Triple
T3260567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Anatomy of a Large-Scale Hypertextual Web Search Engine |
E68398
|
entity |
| Predicate | introduces |
P201
|
FINISHED |
| Object | PageRank |
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 | Statement: [The Anatomy of a Large-Scale Hypertextual Web Search Engine, introduces, PageRank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PageRank Context triple: [The Anatomy of a Large-Scale Hypertextual Web Search Engine, introduces, PageRank]
-
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.
Alexa Internet
Alexa Internet was a web traffic analysis and ranking company best known for providing website popularity metrics and analytics services before its shutdown in 2022.
-
E.
John Mueller
John Mueller is a well-known webmaster trends analyst and public-facing representative for Google Search, recognized for providing guidance to website owners and SEOs about Google's indexing and ranking practices.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafa673a481909b5024b4e0e1c2a7 |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e8369b708190aeddf21dd9440d6a |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:09 p.m.