Triple

T16497519
Position Surface form Disambiguated ID Type / Status
Subject Matt Sharp E400722 entity
Predicate givenName P17 FINISHED
Object Matt E838977 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: Matt | Statement: [Matt Sharp, givenName, Matt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt
Context triple: [Matt Sharp, givenName, Matt]
  • A. Matt
    Matt is the given name of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
  • B. Matt
    Matt is a fictional character from the dark comedy film "The Opposite of Sex," which follows the chaotic fallout of a manipulative teenager’s impact on the lives of those around her.
  • C. Matt
    Matt is the given name of Canadian-American actor Matt Frewer, best known for portraying the 1980s television character Max Headroom.
  • D. Matt chosen
    Matt is a common masculine given name, often short for Matthew, used in many English-speaking countries.
  • E. Matt Thorr
    Matt Thorr is a musician best known as the bassist for the American glam metal band Ratt.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e343a7c81909e04cbaaa40e2531 completed April 18, 2026, 7:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00582a316c81908ec32679c976ba23 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:14 a.m.