Triple

T19974137
Position Surface form Disambiguated ID Type / Status
Subject La Ciotat E493643 entity
Predicate hasFilmHistoryEvent P2107 FINISHED
Object screenings of early Lumière films LITERAL 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: screenings of early Lumière films | Statement: [La Ciotat, hasFilmHistoryEvent, screenings of early Lumière films]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFilmHistoryEvent
Context triple: [La Ciotat, hasFilmHistoryEvent, screenings of early Lumière films]
  • A. hasPartInFilmHistory
    Indicates that an entity has played a role or contributed in some way to the history or development of film.
  • B. hasHistoricalEvent chosen
    Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
  • C. hasLiveActionFilm
    Indicates that a subject has a corresponding live-action film adaptation or representation.
  • D. filmHistory
    Indicates that there is a historical or background connection between a film and another entity, such as its development, production, or past events related to it.
  • E. hasNotablePersonEvent
    Indicates that there exists a significant event in which the person plays a notable or central role.
  • F. None of above.

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_69da626a67648190af9653832a3aeced completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65bcb72048190aedb4f085ace0493 completed April 20, 2026, 5 p.m.
PD Predicate disambiguation batch_69e537fae79c81909eae39500766d0b6 completed April 19, 2026, 8:15 p.m.
Created at: April 11, 2026, 3:23 p.m.