Triple

T17251479
Position Surface form Disambiguated ID Type / Status
Subject Jinx Johnson E418762 entity
Predicate distributorOfAppearance P52441 FINISHED
Object MGM E179667 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: [Jinx Johnson, distributorOfAppearance, MGM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MGM
Context triple: [Jinx Johnson, distributorOfAppearance, MGM]
  • A. MGM
    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 chosen
    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
    MGM is the three-letter National Rail station code assigned to Metheringham railway station in Lincolnshire, England.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e694f788190a1c86e95264ed2fe completed April 19, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170fb89248190ae431ce51dfeaffd completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.