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.