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AigeoRadar · AI Context Benchmark

AI Context Benchmark

Question → sufficient layer(s) → retrieved slice → measured cost → evidence

Web Tasarım, Özgün Tasarım: Markanızı Benzersiz Kılın

https://onurfreelance.com/ozgun-tasarim-markanizi-benzersiz-kilin

13 questions Answer LLM: unknown ai_context_benchmark_v1

Of 13 questions: lowest measured retrieval cost among sufficient layers — HTML 4 · Schema 1 · AIPM 6 · multi-layer 0 · unanswered 2. Descriptive counts only; no overall ranking.

Of 13 questions: lowest measured retrieval cost among sufficient layers — HTML 4 · Schema 1 · AIPM 6 · multi-layer 0 · unanswered 2. Descriptive counts only; no overall ranking. Each question shows: sufficient layer(s) → retrieved slice → measured input tokens → evidence. Readers interpret; the report does not rank formats. Semantic Redundancy 56% — the manifest repeats the same ideas across fields. This inflates structural size without helping per-question retrieval.

Gold mode · Mixed independent + AIPM consistency

Most Understanding/Retrieval gold comes from HTML. Some questions remain AIPM self-consistency checks (tagged) and are excluded from Understanding when possible. Matching a machine card against its own fields is not evidence that that layer outperforms HTML.

Execution provenance

Methodology
AI Context Benchmark Methodology v1.0
Planner Spec
v1.0
Execution Protocol
v1.0
Question pack
universal_v1
Score version
aipm_benchmark_score_v10
Engine
aipm_benchmark_v4
Answer LLM
unknown / unknown (single provider this lab)
Model snapshot
2026-07
Run id
79d30ed9-73b6-492f-9624-ffc371765002

Question outcomes

Per question: which layers were sufficient, and what was the lowest measured retrieval cost among them. No overall winner.

4

Lowest cost: HTML

1

Lowest cost: Schema

6

Lowest cost: AIPM

0

Multi-layer

2

Unanswered

Manifest design

Semantic Redundancy · 56%

Semantic Redundancy 56% — the manifest repeats the same ideas across fields. This inflates structural size without helping per-question retrieval.

  • →Merge or differentiate `purpose` and `abstract` (100% overlap).
Field A Field B Overlap
purpose abstract 100%
purpose keyFacts 33%
abstract keyFacts 33%

Structural size (secondary)

Structural size is secondary. A larger AIPM is not a failure if per-question retrieval stays tiny — check Semantic Redundancy instead.

HTML · 0 chars
Schema · 0 chars
AIPM · 0 chars

Routing helper (secondary)

Illustrative card-first vs HTML-always simulation — prefer per-question measured cost above. Not a ranking.

Card-first retrieval would use ~21% fewer tokens than HTML-always on this pack (8 answered from machine card, 5 escalated to HTML). Descriptive only.

Orientation pack

9 questions · all layers scored

  • HTML 4/9
  • Schema 2/9
  • AIPM 7/9

Depth pack

4 questions · all layers scored

  • HTML 4/4
  • Schema 0/4
  • AIPM 1/4

Full-context pack metrics (secondary)

These measure the whole file fed to the model this run — not the minimum slice needed per question.

HTML

8/13 matched

6,127 full-pack tokens

Schema

2/13 matched

8,281 full-pack tokens

AIPM

8/13 matched

5,262 full-pack tokens

Full-pack resource table (secondary)

Whole-file context fed this run. Prefer Minimal Retrieval Cost on each question.

Metric HTML Schema AIPM
Coverage (matched) 8/13 2/13 8/13
Context size 0 chars 0 chars 0 chars
Total tokens 6,127 8,281 5,262
Tokens / correct answer 766 4,141 658
Est. cost / correct answer $0.000132 $0.000665 $0.000116
Matched per 1k tokens 1.306 0.242 1.520
Median latency 1,460 ms 1,828 ms 1,443 ms
Est. cost (USD) $0.00106 $0.00133 $0.00093

Six independent scores

Answer Efficiency is the primary cost lens. Accuracy axes remain for research — no combined total or winner.

Answer Efficiency

Matched answers per 1k tokens (and cost per match). The primary efficiency axis — not raw accuracy.

  • HTML 85.9
  • Schema 15.9
  • AIPM 100

Understanding

Can this layer convey what the page is about — using independent HTML gold?

  • HTML 60
  • Schema 20
  • AIPM 60

Retrieval

Can this layer surface shared facts (location, contact, hours, pricing, FAQ, CTA)?

  • HTML 100
  • Schema 0
  • AIPM 25

Evidence

Answer quality vs independent gold (score strength). Partial credit counts; UNKNOWN scores zero unless gold is UNKNOWN.

  • HTML 63.3
  • Schema 18.8
  • AIPM 51.4

Metadata

Language, page kind, and freshness from page signals.

  • HTML 33.3
  • Schema 33.3
  • AIPM 100

Compression

Information delivered per token and context size. Higher means more matched answers for less context cost.

  • HTML 85.9
  • Schema 15.9
  • AIPM 100

Coverage map

AIPM matched 8 question(s) (alone on Q7, Q8, Q9); HTML matched 8. HTML/Schema (or a gap) still needed on Q2, Q3, Q10, Q12, Q13. No layer matched gold on Q2, Q3. Read this as complementary coverage — AIPM orients agents cheaply; HTML supplies depth when the sidecar cannot. HTML 8/13 matched (≈766 tok/match). Schema 2/13 matched (≈4,141 tok/match). AIPM 8/13 matched (≈658 tok/match). Figures are descriptive per layer — not a ranking. See per-question chains for sufficient layers, slice size, and measured cost.

AIPM matched

Q1, Q4, Q5, Q6, Q7, Q8, Q9, Q11

Alone: Q7, Q8, Q9

AIPM insufficient

Q2, Q3, Q10, Q12, Q13

HTML/Schema needed or all layers missed

Unanswered by all

Q2, Q3

HTML layer

Visible page text after stripping AIPM sidecars and JSON-LD. Measures what prose alone can answer.

Context fed: 0 chars

Tokens: 6,127 · median 1,460 ms

Matched this pack: 8/13

Stronger on

Retrieval (100) · Compression (85.9) · Answer Efficiency (85.9)

Weaker on

Metadata (33.3)

Schema layer

JSON-LD structured data with minimal page chrome. Measures what schema markup can answer.

Context fed: 0 chars

Tokens: 8,281 · median 1,828 ms

Matched this pack: 2/13

Stronger on

—

Weaker on

Understanding (20) · Retrieval (0) · Metadata (33.3) · Evidence (18.8) · Compression (15.9) · Answer Efficiency (15.9)

AIPM layer

AI Page Manifest (.ai.json) only. Measures what the machine layer can answer without HTML.

Context fed: 0 chars

Tokens: 5,262 · median 1,443 ms

Matched this pack: 8/13

Stronger on

Metadata (100) · Compression (100) · Answer Efficiency (100)

Weaker on

Retrieval (25)

When to use which layer

AIPM complements HTML — it does not replace full-page prose.

Scenario Recommended Why
Fast orientation (title, purpose, brand, intent) Compare machine card → HTML fallback on this run Machine-card pack: 5,262 tok · $0.00093. Routing sim saved ~21% tokens vs HTML-always.
Deep content / research (prose facts, process detail) HTML (with optional machine orientation) HTML pack: 6,127 tok · $0.00106. Use when depth needs body prose.
Structured entity pulls (org, location, typed fields) Schema.org Schema pack: 8,281 tok · $0.00133. Dense JSON-LD tends to score well here.

Findings

  • —Of 13 questions: lowest measured retrieval cost among sufficient layers — HTML 4 · Schema 1 · AIPM 6 · multi-layer 0 · unanswered 2. Descriptive counts only; no overall ranking.
  • —Semantic Redundancy 56% — the manifest repeats the same ideas across fields. This inflates structural size without helping per-question retrieval.
  • —Manifest design: Merge or differentiate `purpose` and `abstract` (100% overlap).
  • —Structural size is secondary. A larger AIPM is not a failure if per-question retrieval stays tiny — check Semantic Redundancy instead.
  • —AIPM matched 8 question(s) (alone on Q7, Q8, Q9); HTML matched 8. HTML/Schema (or a gap) still needed on Q2, Q3, Q10, Q12, Q13. No layer matched gold on Q2, Q3. Read this as complementary coverage — AIPM orients agents cheaply; HTML supplies depth when the sidecar cannot. HTML 8/13 matched (≈766 tok/match). Schema 2/13 matched (≈4,141 tok/match). AIPM 8/13 matched (≈658 tok/match). Figures are descriptive per layer — not a ranking. See per-question chains for sufficient layers, slice size, and measured cost.

Question-by-question layer analysis

Which layer(s) could answer; which need more or different context; minimum context fed this run.

Q1 · Understanding · orientation

What is the page title?

Gold: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924

Gold source: html.title · html_independent

Sufficient: HTML, AIPM · Needs more / other context: Schema

Measured retrieval cost (API tokens) · lowest cost AIPM · 113 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML title 125 api 1 high yes
Schema name+headline+description+publisher+@type+block 682 api 2 low no
AIPM title 113 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What is the page title?
  2. Planner: Planner mapped question `title` on AIPM to minimal fields: title.
  3. Slice: title — AIPM.title: Özgün Tasarım: Markanızı Benzersiz Kılın
  4. Actual input tokens: 113
  5. LLM answer: Özgün Tasarım: Markanızı Benzersiz Kılın
  6. Evidence: Özgün Tasarım: Markanızı Benzersiz Kılın
  7. Confidence: high · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: What is the page title?
  2. Planner: Planner mapped question `title` on HTML to minimal fields: title.
  3. Slice: title — HTML.title: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924
  4. Actual input tokens: 125
  5. LLM answer: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924
  6. Evidence: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: What is the page title?
  2. Planner: Planner mapped question `title` on SCHEMA to minimal fields: name, headline.
  3. Slice: name+headline+description+publisher+@type+block — SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.headline: \u00d6zg\u00fcn Tasar\u...
  4. Actual input tokens: 682
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 171 in-tok · score 0 · miss

Round 2: 511 in-tok · score 0 · miss

HTML

sufficient

Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924

score 100 · 0 chars context · 125 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 0 chars context · 682 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

sufficient

Özgün Tasarım: Markanızı Benzersiz Kılın

score 87 · 0 chars context · 113 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q2 · Understanding · orientation

What is the primary topic of this page?

Gold: Özgün Tasarım: Markanızı Benzersiz Kılın

Gold source: html.h1 · html_independent

No layer provided a sufficient answer from its context alone.

Measured retrieval cost (API tokens) · lowest cost AIPM · 573 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML h1+title+meta_description+lead_paragraphs+prose_span+body_excerpt 738 api 2 low no
Schema name+description+headline+publisher+@type+block 751 api 2 low no
AIPM primaryTopic+purpose+abstract+title+publisher+keyFacts+audience+contentIntent 573 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: What is the primary topic of this page?
  2. Planner: Planner mapped question `primary_topic` on AIPM to minimal fields: primaryTopic.
  3. Slice: primaryTopic+purpose+abstract+title+publisher+keyFacts+audience+contentIntent — AIPM.primaryTopic: WordPress Eğitimleri ve İpuçları AIPM.purpose: Özgün tasarım, bir markanın kendi...
  4. Actual input tokens: 573
  5. LLM answer: WordPress Eğitimleri ve İpuçları.
  6. Evidence: WordPress Eğitimleri ve İpuçları
  7. Confidence: low · matched no

Round 1: 111 in-tok · score 0 · miss

Round 2: 462 in-tok · score 0 · miss

Execution chain · HTML · 2 round(s)
  1. Question: What is the primary topic of this page?
  2. Planner: Planner mapped question `primary_topic` on HTML to minimal fields: h1, title.
  3. Slice: h1+title+meta_description+lead_paragraphs+prose_span+body_excerpt — HTML.h1: Özgün Tasarım: Markanızı Benzersiz Kılın HTML.title: Özgün Tasarım: Markanızı Benzersiz Kı...
  4. Actual input tokens: 738
  5. LLM answer: The primary topic of this page is unique design and its importance for making a brand distinctive.
  6. Evidence: HTML.h1: Özgün Tasarım: Markanızı Benzersiz Kılın HTML.title: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924 HT...
  7. Confidence: low · matched no

Round 1: 148 in-tok · score 0 · miss

Round 2: 590 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What is the primary topic of this page?
  2. Planner: Planner mapped question `primary_topic` on SCHEMA to minimal fields: name, description.
  3. Slice: name+description+headline+publisher+@type+block — SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.description: \u00d6zg\u00fcn tasa...
  4. Actual input tokens: 751
  5. LLM answer: The primary topic of this page is web design services offered by Onur Freelance.
  6. Evidence: SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00...
  7. Confidence: low · matched no

Round 1: 237 in-tok · score 0 · miss

Round 2: 514 in-tok · score 0 · miss

Root cause · Layer miss

Improve orientation fields; do not paste full HTML into the sidecar.

HTML

insufficient

The primary topic of this page is unique design and its importance for making a brand distinctive.

score 0 · 0 chars context · 738 in-tokens

HTML did not answer from 0 chars of context — additional or different layer context needed.

Schema

insufficient

The primary topic of this page is web design services offered by Onur Freelance.

score 0 · 0 chars context · 751 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

insufficient

WordPress Eğitimleri ve İpuçları.

score 0 · 0 chars context · 573 in-tokens

AIPM did not answer from 0 chars of context — additional or different layer context needed.

Q3 · Understanding · orientation

What is the purpose of this page?

Gold: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakiplerden ayrışmak için önemi büyüktür.

Gold source: html.page_summary · html_independent

Partial: AIPM · Needs more / other context: HTML, Schema

Measured retrieval cost (API tokens) · lowest cost AIPM · 550 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt 866 api 2 low no
Schema description+name+headline+publisher+@type+block 664 api 2 low no
AIPM purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent 550 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: What is the purpose of this page?
  2. Planner: Planner mapped question `purpose` on AIPM to minimal fields: purpose.
  3. Slice: purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent — AIPM.purpose: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir u...
  4. Actual input tokens: 550
  5. LLM answer: Özgün tasarımın bir markanın kendine özgü ve tanınabilir olmasını sağlamak için önemli olduğunu vurgulamak.
  6. Evidence: AIPM.purpose: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakiplerden ayrış...
  7. Confidence: low · matched no

Round 1: 146 in-tok · score 0 · miss

Round 2: 404 in-tok · score 44 · miss

Execution chain · HTML · 2 round(s)
  1. Question: What is the purpose of this page?
  2. Planner: Planner mapped question `purpose` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt — HTML.meta_description: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kri...
  4. Actual input tokens: 866
  5. LLM answer: The purpose of this page is to highlight the importance of unique design in making a brand distinctive and recognizable.
  6. Evidence: HTML.meta_description: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakipler...
  7. Confidence: low · matched no

Round 1: 247 in-tok · score 0 · miss

Round 2: 619 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What is the purpose of this page?
  2. Planner: Planner mapped question `purpose` on SCHEMA to minimal fields: description.
  3. Slice: description+name+headline+publisher+@type+block — SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0...
  4. Actual input tokens: 664
  5. LLM answer: The purpose of this page is to promote unique design services that help brands become distinctive and recognizable.
  6. Evidence: SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0131nabilir olmas\u0131n\u0131 sa\u011fla...
  7. Confidence: low · matched no

Round 1: 214 in-tok · score 0 · miss

Round 2: 450 in-tok · score 0 · miss

Root cause · Partial semantic match

Tighten primaryTopic/purpose/abstract so wording overlaps independent HTML gold.

HTML

insufficient

The purpose of this page is to highlight the importance of unique design in making a brand distinctive and recognizable.

score 0 · 0 chars context · 866 in-tokens

HTML did not answer from 0 chars of context — additional or different layer context needed.

Schema

insufficient

The purpose of this page is to promote unique design services that help brands become distinctive and recognizable.

score 0 · 0 chars context · 664 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

partial

Özgün tasarımın bir markanın kendine özgü ve tanınabilir olmasını sağlamak için önemli olduğunu vurgulamak.

score 44 · 0 chars context · 550 in-tokens

AIPM was only partially aligned with gold from 0 chars of context.

Q4 · Understanding · orientation

Summarize the page in one sentence.

Gold: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakiplerden ayrışmak için önemi büyüktür.

Gold source: html.page_summary · html_independent

Sufficient: HTML, AIPM · Needs more / other context: Schema

Measured retrieval cost (API tokens) · lowest cost AIPM · 551 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs 868 api 2 medium yes
Schema description 666 api 2 low no
AIPM abstract+purpose+primaryTopic+title+publisher+keyFacts+audience+contentIntent 551 api 2 medium yes
Execution chain · AIPM · 2 round(s)
  1. Question: Summarize the page in one sentence.
  2. Planner: Planner mapped question `abstract` on AIPM to minimal fields: abstract.
  3. Slice: abstract+purpose+primaryTopic+title+publisher+keyFacts+audience+contentIntent — AIPM.abstract: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir...
  4. Actual input tokens: 551
  5. LLM answer: Özgün tasarım, markaların kendine özgü ve tanınabilir olmasını sağlayarak rakiplerden ayrışmalarına yardımcı olan kritik bir unsurdur.
  6. Evidence: AIPM.abstract: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakiplerden ayrı...
  7. Confidence: medium · matched yes

Round 1: 146 in-tok · score 39 · miss

Round 2: 405 in-tok · score 62 · match

Execution chain · HTML · 2 round(s)
  1. Question: Summarize the page in one sentence.
  2. Planner: Planner mapped question `abstract` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs — HTML.meta_description: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kri...
  4. Actual input tokens: 868
  5. LLM answer: Özgün tasarım, bir markanın tanınabilirliğini artırarak rakiplerden ayrışmasını sağlayan kritik bir unsurdur.
  6. Evidence: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakiplerden ayrışmak için önemi...
  7. Confidence: medium · matched yes

Round 1: 248 in-tok · score 54 · match

Round 2: 620 in-tok · score 48 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: Summarize the page in one sentence.
  2. Planner: Planner mapped question `abstract` on SCHEMA to minimal fields: description.
  3. Slice: description — SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0...
  4. Actual input tokens: 666
  5. LLM answer: Özgün tasarım, bir markanın tanınabilirliğini artırarak rakiplerinden ayrışmasını sağlayan önemli bir unsurdur.
  6. Evidence: SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0131nabilir olmas\u0131n\u0131 sa\u011fla...
  7. Confidence: low · matched no

Round 1: 215 in-tok · score 39 · miss

Round 2: 451 in-tok · score 0 · miss

HTML

sufficient

Özgün tasarım, bir markanın tanınabilirliğini artırarak rakiplerden ayrışmasını sağlayan kritik bir unsurdur.

score 54 · 0 chars context · 868 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

insufficient

Özgün tasarım, bir markanın tanınabilirliğini artırarak rakiplerinden ayrışmasını sağlayan önemli bir unsurdur.

score 39 · 0 chars context · 666 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

sufficient

Özgün tasarım, markaların kendine özgü ve tanınabilir olmasını sağlayarak rakiplerden ayrışmalarına yardımcı olan kritik bir unsurdur.

score 62 · 0 chars context · 551 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q5 · Understanding · orientation

Who is the publisher or brand?

Gold: Onur Freelance - Web Tasarım Ajansı

Gold source: html.jsonld|title · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 112 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML title 126 api 1 high yes
Schema publisher+name 137 api 1 high yes
AIPM publisher 112 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: Who is the publisher or brand?
  2. Planner: Planner mapped question `publisher` on AIPM to minimal fields: publisher.
  3. Slice: publisher — AIPM.publisher: Onur Freelance - Kurumsal Web Tasarım Ajansı
  4. Actual input tokens: 112
  5. LLM answer: Onur Freelance - Kurumsal Web Tasarım Ajansı.
  6. Evidence: Onur Freelance - Kurumsal Web Tasarım Ajansı
  7. Confidence: high · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: Who is the publisher or brand?
  2. Planner: Planner mapped question `publisher` on HTML to minimal fields: title.
  3. Slice: title — HTML.title: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924
  4. Actual input tokens: 126
  5. LLM answer: Onur Freelance.
  6. Evidence: HTML.title: Özgün Tasarım: Markanızı Benzersiz Kılın - Onur Freelance - 0532 690 9924
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 1 round(s)
  1. Question: Who is the publisher or brand?
  2. Planner: Planner mapped question `publisher` on SCHEMA to minimal fields: publisher, name.
  3. Slice: publisher+name — SCHEMA.publisher: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.name: Onur Freelance - Web T...
  4. Actual input tokens: 137
  5. LLM answer: Onur Freelance - Web Tasarımı Ajansı.
  6. Evidence: Onur Freelance - Web Tasar\u0131m Ajans\u0131
  7. Confidence: high · matched yes

HTML

sufficient

Onur Freelance.

score 83 · 0 chars context · 126 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

sufficient

Onur Freelance - Web Tasarımı Ajansı.

score 80 · 0 chars context · 137 in-tokens

Schema answered using 0 chars of layer context (minimum fed this run).

AIPM

sufficient

Onur Freelance - Kurumsal Web Tasarım Ajansı.

score 91 · 0 chars context · 112 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q6 · Metadata · orientation

What language is this page in?

Gold: tr

Gold source: html.lang|script · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 100 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lang 100 api 1 high yes
Schema inLanguage 100 api 1 high yes
AIPM inLanguage 101 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What language is this page in?
  2. Planner: Planner mapped question `language` on AIPM to minimal fields: inLanguage.
  3. Slice: inLanguage — AIPM.inLanguage: tr
  4. Actual input tokens: 101
  5. LLM answer: tr
  6. Evidence: tr
  7. Confidence: high · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: What language is this page in?
  2. Planner: Planner mapped question `language` on HTML to minimal fields: lang.
  3. Slice: lang — HTML.lang: lang=tr
  4. Actual input tokens: 100
  5. LLM answer: The page is in Turkish (tr).
  6. Evidence: HTML.lang: lang=tr
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 1 round(s)
  1. Question: What language is this page in?
  2. Planner: Planner mapped question `language` on SCHEMA to minimal fields: inLanguage.
  3. Slice: inLanguage — SCHEMA.inLanguage: tr
  4. Actual input tokens: 100
  5. LLM answer: The page is in Turkish (tr).
  6. Evidence: SCHEMA.inLanguage: tr
  7. Confidence: high · matched yes

HTML

sufficient

The page is in Turkish (tr).

score 88 · 0 chars context · 100 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

sufficient

The page is in Turkish (tr).

score 88 · 0 chars context · 100 in-tokens

Schema answered using 0 chars of layer context (minimum fed this run).

AIPM

sufficient

tr

score 100 · 0 chars context · 101 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q7 · Metadata · orientation

What is the content intent?

Gold: informational

Gold source: html.heuristic · html_independent

Sufficient: AIPM · Needs more / other context: HTML, Schema

Measured retrieval cost (API tokens) · lowest cost AIPM · 101 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt 819 api 2 low no
Schema name+description+headline+publisher+@type+block 682 api 2 low no
AIPM contentIntent 101 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What is the content intent?
  2. Planner: Planner mapped question `content_intent` on AIPM to minimal fields: contentIntent.
  3. Slice: contentIntent — AIPM.contentIntent: informational
  4. Actual input tokens: 101
  5. LLM answer: The content intent is informational.
  6. Evidence: AIPM.contentIntent: informational
  7. Confidence: high · matched yes
Execution chain · HTML · 2 round(s)
  1. Question: What is the content intent?
  2. Planner: Planner mapped question `content_intent` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt — HTML.meta_description: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kri...
  4. Actual input tokens: 819
  5. LLM answer: The content intent is to highlight the importance of unique design in making a brand distinctive and recognizable.
  6. Evidence: HTML.meta_description: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakipler...
  7. Confidence: low · matched no

Round 1: 245 in-tok · score 0 · miss

Round 2: 574 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What is the content intent?
  2. Planner: Planner mapped question `content_intent` on SCHEMA to minimal fields: name, description.
  3. Slice: name+description+headline+publisher+@type+block — SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.description: \u00d6zg\u00fcn tasa...
  4. Actual input tokens: 682
  5. LLM answer: The content intent is to promote unique design services that help brands stand out and become recognizable.
  6. Evidence: SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00...
  7. Confidence: low · matched no

Round 1: 234 in-tok · score 0 · miss

Round 2: 448 in-tok · score 0 · miss

HTML

insufficient

The content intent is to highlight the importance of unique design in making a brand distinctive and recognizable.

score 0 · 0 chars context · 819 in-tokens

HTML did not answer from 0 chars of context — additional or different layer context needed.

Schema

insufficient

The content intent is to promote unique design services that help brands stand out and become recognizable.

score 0 · 0 chars context · 682 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

sufficient

The content intent is informational.

score 88 · 0 chars context · 101 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q8 · Metadata · orientation

What page type is declared in the machine layer?

Gold: blog

Gold source: pageType · aipm_consistency

Sufficient: AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 104 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+title+h1+meta_description+prose_span+body_excerpt 776 api 2 low no
Schema @type+name+headline+description+publisher+block 619 api 2 low no
AIPM pageType 104 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What page type is declared in the machine layer?
  2. Planner: Planner mapped question `page_type` on AIPM to minimal fields: pageType.
  3. Slice: pageType — AIPM.pageType: blog
  4. Actual input tokens: 104
  5. LLM answer: blog
  6. Evidence: blog
  7. Confidence: high · matched yes
Execution chain · HTML · 2 round(s)
  1. Question: What page type is declared in the machine layer?
  2. Planner: Planner mapped question `page_type` on HTML to minimal fields: lead_paragraphs.
  3. Slice: lead_paragraphs+title+h1+meta_description+prose_span+body_excerpt — HTML.lead_paragraphs: Ana Sayfa » WordPress Eğitimleri ve İpuçları » Özgün Tasarım: Markanızı Benzer...
  4. Actual input tokens: 776
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 199 in-tok · score 0 · miss

Round 2: 577 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What page type is declared in the machine layer?
  2. Planner: Planner mapped question `page_type` on SCHEMA to minimal fields: @type.
  3. Slice: @type+name+headline+description+publisher+block — SCHEMA.@type: PostalAddress SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.head...
  4. Actual input tokens: 619
  5. LLM answer: PostalAddress
  6. Evidence: PostalAddress
  7. Confidence: low · matched no

Round 1: 104 in-tok · score 0 · miss

Round 2: 515 in-tok · score 0 · miss

HTML

skipped

UNKNOWN.

score 0 · 0 chars context · 0 in-tokens

Skipped (AIPM-only).

Schema

skipped

PostalAddress

score 0 · 0 chars context · 0 in-tokens

Skipped (AIPM-only).

AIPM

sufficient

blog

score 100 · 0 chars context · 104 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q9 · Understanding · orientation

Who is the intended audience declared in AIPM?

Gold: Kurumsal web sitesi, WordPress web tasarım, e-ticaret sitesi, SEO hizmeti, dijital pazarlama desteği arayan KOBİ’ler, yerel işletmeler, hizmet firmaları, klinikler, hukuk büroları, eğitim kurumları, üretici firmalar, yeni marka kurmak isteyen girişimciler.

Gold source: audience · aipm_consistency

Sufficient: AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 651 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+title+h1+meta_description+prose_span+body_excerpt 849 api 2 low no
Schema name+description+headline+publisher+@type+block 692 api 2 low no
AIPM audience+purpose+abstract+primaryTopic+title+publisher+keyFacts+contentIntent 651 api 2 medium yes
Execution chain · AIPM · 2 round(s)
  1. Question: Who is the intended audience declared in AIPM?
  2. Planner: Planner mapped question `audience` on AIPM to minimal fields: audience.
  3. Slice: audience+purpose+abstract+primaryTopic+title+publisher+keyFacts+contentIntent — AIPM.audience: ["Kurumsal web sitesi","WordPress web tasarım","e-ticaret sitesi","SEO hizmeti","diji...
  4. Actual input tokens: 651
  5. LLM answer: The intended audience includes KOBİ’ler, yerel işletmeler, hizmet firmaları, klinikler, hukuk büroları, eğitim kurumları, üretici firmalar, and girişimciler.
  6. Evidence: AIPM.audience: ["Kurumsal web sitesi","WordPress web tasarım","e-ticaret sitesi","SEO hizmeti","dijital pazarlama desteği arayan KOBİ’ler","...
  7. Confidence: medium · matched yes

Round 1: 187 in-tok · score 55 · miss

Round 2: 464 in-tok · score 60 · match

Execution chain · HTML · 2 round(s)
  1. Question: Who is the intended audience declared in AIPM?
  2. Planner: Planner mapped question `audience` on HTML to minimal fields: lead_paragraphs.
  3. Slice: lead_paragraphs+title+h1+meta_description+prose_span+body_excerpt — HTML.lead_paragraphs: Ana Sayfa » WordPress Eğitimleri ve İpuçları » Özgün Tasarım: Markanızı Benzer...
  4. Actual input tokens: 849
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 200 in-tok · score 0 · miss

Round 2: 649 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: Who is the intended audience declared in AIPM?
  2. Planner: Planner mapped question `audience` on SCHEMA to minimal fields: name, description.
  3. Slice: name+description+headline+publisher+@type+block — SCHEMA.name: Onur Freelance - Web Tasar\u0131m Ajans\u0131 SCHEMA.description: \u00d6zg\u00fcn tasa...
  4. Actual input tokens: 692
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 239 in-tok · score 0 · miss

Round 2: 453 in-tok · score 0 · miss

HTML

skipped

UNKNOWN.

score 0 · 0 chars context · 0 in-tokens

Skipped (AIPM-only).

Schema

skipped

UNKNOWN.

score 0 · 0 chars context · 0 in-tokens

Skipped (AIPM-only).

AIPM

sufficient

The intended audience includes KOBİ’ler, yerel işletmeler, hizmet firmaları, klinikler, hukuk büroları, eğitim kurumları, üretici firmalar, and girişimciler.

score 60 · 0 chars context · 651 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q10 · Retrieval · depth

Which location or city is mentioned for this business?

Gold: İstanbul

Gold source: html.address|prose · html_independent

Sufficient: HTML · Needs more / other context: Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 104 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML prose_span 104 api 1 high yes
Schema addressLocality+name+headline+description+publisher+@type+block 592 api 2 low no
AIPM purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent 463 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: Which location or city is mentioned for this business?
  2. Planner: Planner mapped question `geo_signal` on AIPM to minimal fields: geo, areaServed, address.
  3. Slice: purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent — AIPM.purpose: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir u...
  4. Actual input tokens: 463
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 0 in-tok · score 0 · miss

Round 2: 463 in-tok · score 0 · miss

Execution chain · HTML · 1 round(s)
  1. Question: Which location or city is mentioned for this business?
  2. Planner: Planner mapped question `geo_signal` on HTML to minimal fields: prose_span.
  3. Slice: prose_span — HTML.prose_span: İstanbul
  4. Actual input tokens: 104
  5. LLM answer: İstanbul
  6. Evidence: İstanbul
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: Which location or city is mentioned for this business?
  2. Planner: Planner mapped question `geo_signal` on SCHEMA to minimal fields: address, addressLocality, areaServed.
  3. Slice: addressLocality+name+headline+description+publisher+@type+block — SCHEMA.addressLocality: G\u00fcleken Sokak No 6 Daire 1 SCHEMA.name: Onur Freelance - Web Tasar\u01...
  4. Actual input tokens: 592
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 118 in-tok · score 0 · miss

Round 2: 474 in-tok · score 0 · miss

Root cause · Depth gap (expected)

Prose/detail questions belong to HTML — escalate after AIPM orientation.

HTML

sufficient

İstanbul

score 100 · 0 chars context · 104 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 0 chars context · 592 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 0 chars context · 463 in-tokens

AIPM did not answer from 0 chars of context — additional or different layer context needed.

Q11 · Retrieval · depth

According to the page, what does it say about: "Herhangi bir alanda öne çıkmak ve rakiplerden ay…"?

Gold: Herhangi bir alanda öne çıkmak ve rakiplerden ayrışmak için özgün tasarımın önemi büyüktür.

Gold source: html.prose · html_independent

Sufficient: HTML, AIPM · Needs more / other context: Schema

Measured retrieval cost (API tokens) · lowest cost HTML · 148 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML prose_span 148 api 1 high yes
Schema description+block+name+headline+publisher+@type 831 api 2 low no
AIPM keyFacts 223 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: According to the page, what does it say about: "Herhangi bir alanda öne çıkmak ve rakiplerden ay…"?
  2. Planner: Planner mapped question `page_fact_1` on AIPM to minimal fields: keyFacts, sections.
  3. Slice: keyFacts — AIPM.keyFacts: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir...
  4. Actual input tokens: 223
  5. LLM answer: Öne çıkmak ve rakiplerden ayrışmak için özgün tasarımın önemi büyüktür.
  6. Evidence: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir unsurdur. Öne çıkmak ve rakiplerden ayrışmak için önemi...
  7. Confidence: high · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: According to the page, what does it say about: "Herhangi bir alanda öne çıkmak ve rakiplerden ay…"?
  2. Planner: Planner mapped question `page_fact_1` on HTML to minimal fields: prose_span.
  3. Slice: prose_span — HTML.prose_span: Herhangi bir alanda öne çıkmak ve rakiplerden ayrışmak için özgün tasarımın önemi b...
  4. Actual input tokens: 148
  5. LLM answer: Özgün tasarımın, herhangi bir alanda öne çıkmak ve rakiplerden ayrışmak için büyük önemi olduğu belirtiliyor.
  6. Evidence: HTML.prose_span: Herhangi bir alanda öne çıkmak ve rakiplerden ayrışmak için özgün tasarımın önemi büyüktür.
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: According to the page, what does it say about: "Herhangi bir alanda öne çıkmak ve rakiplerden ay…"?
  2. Planner: Planner mapped question `page_fact_1` on SCHEMA to minimal fields: description, block.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0...
  4. Actual input tokens: 831
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 361 in-tok · score 0 · miss

Round 2: 470 in-tok · score 0 · miss

HTML

sufficient

Özgün tasarımın, herhangi bir alanda öne çıkmak ve rakiplerden ayrışmak için büyük önemi olduğu belirtiliyor.

score 83 · 0 chars context · 148 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 0 chars context · 831 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

sufficient

Öne çıkmak ve rakiplerden ayrışmak için özgün tasarımın önemi büyüktür.

score 93 · 0 chars context · 223 in-tokens

AIPM answered using 0 chars of layer context (minimum fed this run).

Q12 · Retrieval · depth

According to the page, what does it say about: "Marka Kimliği ve Farkındalık: Özgün tasarım, mar…"?

Gold: Marka Kimliği ve Farkındalık: Özgün tasarım, markanın kendine özgü kimliğini yansıtır.

Gold source: html.prose · html_independent

Sufficient: HTML · Needs more / other context: Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 151 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML prose_span 151 api 1 high yes
Schema description+block+name+headline+publisher+@type 837 api 2 low no
AIPM keyFacts+purpose+abstract+primaryTopic+title+publisher+audience+contentIntent 710 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: According to the page, what does it say about: "Marka Kimliği ve Farkındalık: Özgün tasarım, mar…"?
  2. Planner: Planner mapped question `page_fact_2` on AIPM to minimal fields: keyFacts, sections.
  3. Slice: keyFacts+purpose+abstract+primaryTopic+title+publisher+audience+contentIntent — AIPM.keyFacts: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir...
  4. Actual input tokens: 710
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 226 in-tok · score 0 · miss

Round 2: 484 in-tok · score 0 · miss

Execution chain · HTML · 1 round(s)
  1. Question: According to the page, what does it say about: "Marka Kimliği ve Farkındalık: Özgün tasarım, mar…"?
  2. Planner: Planner mapped question `page_fact_2` on HTML to minimal fields: prose_span.
  3. Slice: prose_span — HTML.prose_span: Marka Kimliği ve Farkındalık: Özgün tasarım, markanın kendine özgü kimliğini yansıt...
  4. Actual input tokens: 151
  5. LLM answer: Özgün tasarım, markanın kendine özgü kimliğini yansıtır.
  6. Evidence: Marka Kimliği ve Farkındalık: Özgün tasarım, markanın kendine özgü kimliğini yansıtır.
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: According to the page, what does it say about: "Marka Kimliği ve Farkındalık: Özgün tasarım, mar…"?
  2. Planner: Planner mapped question `page_fact_2` on SCHEMA to minimal fields: description, block.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0...
  4. Actual input tokens: 837
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 364 in-tok · score 0 · miss

Round 2: 473 in-tok · score 0 · miss

Root cause · Depth gap (expected)

Prose/detail questions belong to HTML — escalate after AIPM orientation.

HTML

sufficient

Özgün tasarım, markanın kendine özgü kimliğini yansıtır.

score 90 · 0 chars context · 151 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 0 chars context · 837 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 0 chars context · 710 in-tokens

AIPM did not answer from 0 chars of context — additional or different layer context needed.

Q13 · Retrieval · depth

According to the page, what does it say about: "Benzersiz bir tasarım, markanın farkındalığını a…"?

Gold: Benzersiz bir tasarım, markanın farkındalığını artırır ve hedef kitlenin zihninde iz bırakır.

Gold source: html.prose · html_independent

Sufficient: HTML · Needs more / other context: Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 148 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML prose_span 148 api 1 high yes
Schema description+block+name+headline+publisher+@type 833 api 2 low no
AIPM keyFacts+purpose+abstract+primaryTopic+title+publisher+audience+contentIntent 706 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: According to the page, what does it say about: "Benzersiz bir tasarım, markanın farkındalığını a…"?
  2. Planner: Planner mapped question `page_fact_3` on AIPM to minimal fields: keyFacts, sections.
  3. Slice: keyFacts+purpose+abstract+primaryTopic+title+publisher+audience+contentIntent — AIPM.keyFacts: Özgün tasarım, bir markanın kendine özgü ve tanınabilir olmasını sağlayan kritik bir...
  4. Actual input tokens: 706
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 224 in-tok · score 0 · miss

Round 2: 482 in-tok · score 0 · miss

Execution chain · HTML · 1 round(s)
  1. Question: According to the page, what does it say about: "Benzersiz bir tasarım, markanın farkındalığını a…"?
  2. Planner: Planner mapped question `page_fact_3` on HTML to minimal fields: prose_span.
  3. Slice: prose_span — HTML.prose_span: Benzersiz bir tasarım, markanın farkındalığını artırır ve hedef kitlenin zihninde i...
  4. Actual input tokens: 148
  5. LLM answer: Benzersiz bir tasarım, markanın farkındalığını artırır ve hedef kitlenin zihninde iz bırakır.
  6. Evidence: Benzersiz bir tasarım, markanın farkındalığını artırır ve hedef kitlenin zihninde iz bırakır.
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: According to the page, what does it say about: "Benzersiz bir tasarım, markanın farkındalığını a…"?
  2. Planner: Planner mapped question `page_fact_3` on SCHEMA to minimal fields: description, block.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: \u00d6zg\u00fcn tasar\u0131m, bir markan\u0131n kendine \u00f6zg\u00fc ve tan\u0...
  4. Actual input tokens: 833
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 362 in-tok · score 0 · miss

Round 2: 471 in-tok · score 0 · miss

Root cause · Depth gap (expected)

Prose/detail questions belong to HTML — escalate after AIPM orientation.

HTML

sufficient

Benzersiz bir tasarım, markanın farkındalığını artırır ve hedef kitlenin zihninde iz bırakır.

score 100 · 0 chars context · 148 in-tokens

HTML answered using 0 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 0 chars context · 833 in-tokens

Schema did not answer from 0 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 0 chars context · 706 in-tokens

AIPM did not answer from 0 chars of context — additional or different layer context needed.

Methodology

  • AI Context Benchmark: Planner → Slice → LLM with measured API input tokens.
  • Reports describe sufficient layers, slice size, cost, and evidence — they do not declare a winning format.
  • Layers under test today: HTML, Schema.org, AIPM (extensible to RSS, Markdown, PDF, …).
  • Engine aipm_benchmark_v4 · Wed, Jul 29, 2026 12:54 PM · aipm_benchmark_score_v10

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