Triple

T1432861
Position Surface form Disambiguated ID Type / Status
Subject Michael Beach E30488 entity
Predicate notableWork P4 FINISHED
Object The Abyss E159007 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: The Abyss | Statement: [Michael Beach, notableWork, The Abyss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Abyss
Context triple: [Michael Beach, notableWork, The Abyss]
  • A. The Abyss chosen
    The Abyss is a 1989 science fiction film directed by James Cameron that follows a deep-sea oil drilling team encountering mysterious underwater phenomena.
  • B. Waterworld
    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.
  • C. The Deep
    The Deep is a 1976 adventure novel by Peter Benchley that follows a young couple who discover dangerous secrets and sunken treasure while diving near Bermuda.
  • D. The Deep
    The Deep is a striking futuristic aquarium and marine research center in Kingston upon Hull, England, known for its dramatic architecture and extensive collection of marine life.
  • E. Sirena Deep
    Sirena Deep is one of the deepest known points in the world's oceans, located within the Mariana Trench in the western Pacific Ocean.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4ddbe208190a68cb000a6970d17 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad016e25808190880a6e637dd2590a completed March 8, 2026, 4:56 a.m.
Created at: March 1, 2026, 8 p.m.