Triple

T17747727
Position Surface form Disambiguated ID Type / Status
Subject Dichen Lachman E443030 entity
Predicate notableWork P4 FINISHED
Object Aquamarine 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: Aquamarine | Statement: [Dichen Lachman, notableWork, Aquamarine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aquamarine
Context triple: [Dichen Lachman, notableWork, Aquamarine]
  • A. Aquamarine
    Aquamarine is a blue to blue-green variety of the mineral beryl, prized as a gemstone for its clear, sea-colored appearance.
  • B. Aquamarine chosen
    Aquamarine is a 2006 teen fantasy romantic comedy film about two best friends who discover a mermaid in a swimming pool.
  • C. Sapphire
    Sapphire is an American author best known for her novel "Push," which was adapted into the acclaimed film "Precious."
  • D. Sapphire
    Sapphire is a 1959 British crime drama film that explores racial tensions and prejudice in London through the investigation of a young woman's murder.
  • E. Sapphire
    Sapphire is a precious gemstone variety of the mineral corundum, typically blue, valued for its hardness, brilliance, and use in fine jewelry and industrial applications.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47ad33160819093c9bbd3c8957314 completed April 19, 2026, 6:48 a.m.
Created at: April 10, 2026, 10:10 a.m.