Triple

T4264147
Position Surface form Disambiguated ID Type / Status
Subject Thomas Matthew E96182 entity
Predicate notableWork P4 FINISHED
Object Matthew Bible E17635 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 Bible | Statement: [Thomas Matthew, notableWork, Matthew Bible]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Bible
Context triple: [Thomas Matthew, notableWork, Matthew Bible]
  • A. Matthew Bible chosen
    The Matthew Bible is an early English translation of the Bible, first published in 1537 and largely based on the work of William Tyndale and Myles Coverdale.
  • B. Alan Bible
    Alan Bible was a long-serving U.S. Senator from Nevada known for his influence on public lands and conservation policy.
  • 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. 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.
  • E. Matthew
    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.
  • 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_69b3454095ac81909c2494f7ff294af1 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34fc94f64819091f438d8ae5ed687 completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b79455f48190b48b1359b223e0f7 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:06 p.m.