Triple

T4864321
Position Surface form Disambiguated ID Type / Status
Subject Harvard Film Archive E108730 entity
Predicate hasScreeningVenue P51034 FINISHED
Object cinema theater at Harvard University 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: cinema theater at Harvard University | Statement: [Harvard Film Archive, hasScreeningVenue, cinema theater at Harvard University]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasScreeningVenue
Context triple: [Harvard Film Archive, hasScreeningVenue, cinema theater at Harvard University]
  • A. screeningVenue chosen
    Indicates the place or location where a screening (such as a film or event showing) takes place.
  • B. hasEntertainmentVenue
    Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
  • C. hasAttachedVenue
    Indicates that one entity has another entity linked or associated with it as a venue.
  • D. hasTicketHall
    Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
  • E. hasVenueContext
    Indicates that an entity is associated with a particular venue or setting that provides contextual information about where it occurs or is situated.
  • 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_69bd440b965081908b0557721cae6338 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d7718e48190af4c0d1abfa87795 completed March 20, 2026, 3:53 p.m.
PD Predicate disambiguation batch_69bd6c27334481909ba8ac80854f7d8e completed March 20, 2026, 3:47 p.m.
Created at: March 20, 2026, 1:26 p.m.