Triple

T2866558
Position Surface form Disambiguated ID Type / Status
Subject Princeton Science Library E63453 entity
Predicate hasNotableAuthor P4244 FINISHED
Object Ian Stewart E143784 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: Ian Stewart | Statement: [Princeton Science Library, hasNotableAuthor, Ian Stewart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ian Stewart
Context triple: [Princeton Science Library, hasNotableAuthor, Ian Stewart]
  • A. Ian Stewart chosen
    Ian Stewart is a British mathematician and prolific popular science writer known for his engaging books and articles on mathematics and its applications.
  • B. Alan Cruttenden
    Alan Cruttenden is a British phonetician and linguist known for his influential work on English pronunciation and intonation, including editing later editions of the Cambridge English Pronouncing Dictionary.
  • C. Alan Stewart
    Alan Stewart is a cinematographer known for his work on major feature films, including collaborations with director Guy Ritchie.
  • D. Alasdair Steedman
    Alasdair Steedman was a senior Royal Air Force officer who rose to high command, including leadership of the RAF’s Fighter Command.
  • E. Christopher Holmes
    Christopher Holmes is an editor known for his work on the film "Five Easy Pieces."
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfbb7ed4819096ca65391077e2af completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01da85930819092d19a5e712cfa18 completed March 10, 2026, 1:33 p.m.
Created at: March 6, 2026, 10:02 p.m.