Triple

T21481792
Position Surface form Disambiguated ID Type / Status
Subject Matt Mattox E530010 entity
Predicate givenName P17 FINISHED
Object Matt NE NERFINISHED

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 Mattox, givenName, Matt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt
Context triple: [Matt Mattox, 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
    Matt is the idealistic young romantic lead in the long-running musical "The Fantasticks," whose journey explores love, disillusionment, and maturity.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45acc3881908e38d3f28964152b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea338f988190a3044f8d02a567fe completed April 23, 2026, 9:45 a.m.
Created at: April 16, 2026, 6:21 p.m.