Triple

T11985501
Position Surface form Disambiguated ID Type / Status
Subject Martin Short E285266 entity
Predicate name P16 FINISHED
Object Martin Short E285266 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: Martin Short | Statement: [Martin Short, name, Martin Short]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin Short
Context triple: [Martin Short, name, Martin Short]
  • A. Martin Short chosen
    Martin Short is a Canadian-American comedian and actor renowned for his energetic characters and work on sketch comedy shows, films, and Broadway.
  • B. Al Murray
    Al Murray is a British comedian and television personality best known for his pub landlord character and sharp, observational stand-up comedy.
  • C. Chris Elliott
    Chris Elliott is an American actor and comedian known for his offbeat roles in film and television, including his supporting role in the comedy classic "Groundhog Day."
  • D. Will Murray
    Will Murray is an American writer best known for his extensive work continuing classic pulp fiction series, particularly the Doc Savage novels.
  • E. Jonathan Winters
    Jonathan Winters was an influential American comedian and actor renowned for his improvisational genius, character work, and pioneering impact on modern stand-up and sketch comedy.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903acbb9081908fe7f8360057785c completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47237c23081909044388ff5dc73b3 completed May 1, 2026, 9:28 a.m.
Created at: April 8, 2026, 9:46 p.m.