Triple

T13430437
Position Surface form Disambiguated ID Type / Status
Subject Franck Eggelhoffer E313592 entity
Predicate portrayedBy P1507 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: [Franck Eggelhoffer, portrayedBy, Martin Short]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin Short
Context triple: [Franck Eggelhoffer, portrayedBy, 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaed304ac8190a8021f749de8164c completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7398b828c8190a029a5862ae1fded completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:40 p.m.