Triple

T15894218
Position Surface form Disambiguated ID Type / Status
Subject Margaret Booth E385409 entity
Predicate employer P7 FINISHED
Object MGM E10100 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: MGM | Statement: [Margaret Booth, employer, MGM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MGM
Context triple: [Margaret Booth, employer, MGM]
  • A. MGM chosen
    MGM (Metro-Goldwyn-Mayer) is a historic American film studio renowned for its iconic roaring lion logo and for producing many of the most famous movies of Hollywood’s Golden Age.
  • B. MGM
    MGM is a major American entertainment and hospitality brand best known for its iconic casinos, resorts, and film studio legacy.
  • C. MGM
    MGM is the IATA airport code for Montgomery Regional Airport, the primary commercial airport serving Montgomery, Alabama.
  • D. MGM
    MGM is the three-letter FAA location identifier assigned to Harbor Springs Municipal Airport in Michigan.
  • E. MGM Holdings
    MGM Holdings is the parent company that owns and oversees Metro-Goldwyn-Mayer’s entertainment assets and operations.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563809748190a54156b946d3f061 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0497cb481908e8ea4ebb9c4039d completed May 9, 2026, 10:08 p.m.
Created at: April 10, 2026, 4:51 a.m.