Triple

T2120810
Position Surface form Disambiguated ID Type / Status
Subject Tonga-Kermadec subduction system E43916 entity
Predicate contains P35 FINISHED
Object Horizon Deep E43915 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: Horizon Deep | Statement: [Tonga-Kermadec subduction system, contains, Horizon Deep]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Horizon Deep
Context triple: [Tonga-Kermadec subduction system, contains, Horizon Deep]
  • A. Horizon Deep chosen
    Horizon Deep is the deepest known point in the Tonga Trench and one of the deepest locations in the world's oceans.
  • B. 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.
  • 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. Horizons
    Horizons is a French centre-right political party founded by former prime minister Édouard Philippe, generally aligned with President Emmanuel Macron’s centrist majority.
  • E. Horizons
    Horizons was a beloved Epcot dark ride that offered guests an immersive, optimistic vision of future living through detailed scenes and advanced audio-animatronics.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb3404348190bc843022fbd2b4d0 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5197259c8190bffbbb4abaaddfd0 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:44 p.m.