Triple

T19876413
Position Surface form Disambiguated ID Type / Status
Subject Helen E477648 entity
Predicate firstAppearance P795 FINISHED
Object Waterworld (1995 film) NE NERFINISHED

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: Waterworld (1995 film) | Statement: [Helen, firstAppearance, Waterworld (1995 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterworld (1995 film)
Context triple: [Helen, firstAppearance, Waterworld (1995 film)]
  • A. Waterworld chosen
    Waterworld is a 1995 post-apocalyptic science fiction film set on a flooded Earth, best known for its ambitious water-based production, high budget, and starring Kevin Costner as a mutant drifter.
  • B. Water World
    Water World is the water park section of Waldameer Park, featuring a variety of water slides, pools, and aquatic attractions.
  • C. The Abyss
    The Abyss is a 1910 Danish silent drama film that made Asta Nielsen an international star and is renowned for its intense portrayal of passion and sexuality.
  • D. The Abyss
    The Abyss is a 1989 science fiction film directed by James Cameron that follows a deep-sea oil drilling team encountering mysterious underwater phenomena.
  • E. Water (2005 film)
    Water (2005 film) is a critically acclaimed Indian drama directed by Deepa Mehta that explores the lives of Hindu widows in 1930s colonial India.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658dbdb648190b423865e7994a8fe completed April 20, 2026, 4:48 p.m.
Created at: April 10, 2026, 1:52 p.m.