Triple

T13756289
Position Surface form Disambiguated ID Type / Status
Subject Dany Heatley E330481 entity
Predicate familyName P18 FINISHED
Object Heatley E1059021 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: Heatley | Statement: [Dany Heatley, familyName, Heatley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heatley
Context triple: [Dany Heatley, familyName, Heatley]
  • A. Heatley chosen
    Heatley is a surname most prominently associated with former NHL star forward Dany Heatley, known for his prolific goal-scoring career.
  • B. Heiss
    Heiss is the surname of Alanna Heiss, an influential American curator and founder of New York’s pioneering contemporary art institution MoMA PS1.
  • C. Hochkalter
    Hochkalter is a prominent mountain peak in the Bavarian Alps of southeastern Germany, known for its rugged limestone formations and popular alpine climbing routes.
  • D. Hitzig
    Hitzig is a German surname most notably associated with 19th-century figures such as architect Friedrich Hitzig.
  • E. Garm Hava
    Garm Hava is a landmark 1973 Indian film that poignantly portrays the struggles of a Muslim family in post-Partition India and is widely regarded as a classic of Indian parallel cinema.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de022286b481908f8a801042743512 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b06faed88190abc44e6256cb9301 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 10:09 p.m.