Triple
T14371451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RankBrain |
E356366
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object |
Google search ranking system
The Google search ranking system is a complex, AI-driven framework that evaluates and orders web pages in search results based on hundreds of signals like relevance, quality, and user intent.
|
E1095354
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Google search ranking system | Statement: [RankBrain, partOf, Google search ranking system]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Google search ranking system Context triple: [RankBrain, partOf, Google search ranking system]
-
A.
Google Search indexing systems
Google Search indexing systems are the complex set of algorithms and infrastructure Google uses to crawl, process, and organize web content so it can be efficiently retrieved and ranked in search results.
-
B.
PageRank algorithm
The PageRank algorithm is a link analysis method used by search engines, notably Google, to rank web pages in search results based on their importance within the web’s link structure.
-
C.
RankBrain
RankBrain is a machine-learning-based component of Google's search engine that helps interpret and process search queries to deliver more relevant results.
-
D.
The Anatomy of a Large-Scale Hypertextual Web Search Engine
"The Anatomy of a Large-Scale Hypertextual Web Search Engine" is a seminal research paper by Sergey Brin and Larry Page that introduced the design and PageRank algorithm behind the early Google search engine.
-
E.
AltaVista
AltaVista was one of the earliest and most popular web search engines of the 1990s, known for its fast, comprehensive internet search before being eclipsed by later competitors.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Google search ranking system Triple: [RankBrain, partOf, Google search ranking system]
Generated description
The Google search ranking system is a complex, AI-driven framework that evaluates and orders web pages in search results based on hundreds of signals like relevance, quality, and user intent.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Google search ranking system Target entity description: The Google search ranking system is a complex, AI-driven framework that evaluates and orders web pages in search results based on hundreds of signals like relevance, quality, and user intent.
-
A.
Google Search indexing systems
Google Search indexing systems are the complex set of algorithms and infrastructure Google uses to crawl, process, and organize web content so it can be efficiently retrieved and ranked in search results.
-
B.
PageRank algorithm
The PageRank algorithm is a link analysis method used by search engines, notably Google, to rank web pages in search results based on their importance within the web’s link structure.
-
C.
RankBrain
RankBrain is a machine-learning-based component of Google's search engine that helps interpret and process search queries to deliver more relevant results.
-
D.
The Anatomy of a Large-Scale Hypertextual Web Search Engine
"The Anatomy of a Large-Scale Hypertextual Web Search Engine" is a seminal research paper by Sergey Brin and Larry Page that introduced the design and PageRank algorithm behind the early Google search engine.
-
E.
AltaVista
AltaVista was one of the earliest and most popular web search engines of the 1990s, known for its fast, comprehensive internet search before being eclipsed by later competitors.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fb2082c8190b42cc5f2bab4f574 |
completed | April 14, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c5363a081909681b54c1d8218dc |
completed | May 8, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fd4e795948819097c43e30902f1654 |
completed | May 8, 2026, 2:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4f04d7ec819095b64d4811440166 |
completed | May 8, 2026, 2:48 a.m. |
Created at: April 10, 2026, 1:15 a.m.