Triple

T5373423
Position Surface form Disambiguated ID Type / Status
Subject Protestant Bible E108903 entity
Predicate containsBook P5478 FINISHED
Object Matthew E111324 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: Matthew | Statement: [Protestant Bible, containsBook, Matthew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew
Context triple: [Protestant Bible, containsBook, Matthew]
  • A. Matthew
    Matthew is the given name of Sir Matt Busby, the legendary Scottish football manager best known for his long and successful tenure at Manchester United.
  • B. Matthew chosen
    Matthew is traditionally recognized as one of the Twelve Apostles of Jesus and is commonly associated with the authorship of the Gospel of Matthew in the New Testament.
  • C. Matthew
    Matthew is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s intricate romantic mystery.
  • D. James
    James is a common masculine given name of Hebrew origin meaning "supplanter," widely used in English-speaking countries.
  • E. James
    James is a prominent early Christian figure, traditionally identified as James the brother of Jesus and a leader in the Jerusalem church.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86abc1e88190ad08279c3bf238e5 completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf293850c48190bd0cdab64368157f completed March 21, 2026, 11:26 p.m.
Created at: March 20, 2026, 2:03 p.m.