Triple
T13421579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eigenfactor Score |
E313370
|
entity |
| Predicate | similarTo |
P4460
|
FINISHED |
| Object | PageRank algorithm |
E66951
|
NE FINISHED |
How this triple was built (2 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: PageRank algorithm | Statement: [Eigenfactor Score, similarTo, PageRank algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PageRank algorithm Context triple: [Eigenfactor Score, similarTo, PageRank algorithm]
-
A.
PageRank algorithm
chosen
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.
-
B.
HITS algorithm
The HITS algorithm is a link analysis method that ranks web pages by separately evaluating their authority and hub scores based on the structure of hyperlinks.
-
C.
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.
-
D.
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.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb98e808190948013e8f24779c6 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7308493e481909da52f8bbcc0bd6b |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:39 p.m.