Triple

T15513681
Position Surface form Disambiguated ID Type / Status
Subject Michael S. Hart E368776 entity
Predicate familyName P18 FINISHED
Object Hart E55151 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: Hart | Statement: [Michael S. Hart, familyName, Hart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hart
Context triple: [Michael S. Hart, familyName, Hart]
  • A. Hart chosen
    Hart is a surname most famously associated with Moss Hart, the acclaimed American playwright and theater director known for works like "You Can't Take It with You" and "Once in a Lifetime."
  • B. Hart
    Hart is a local government district and civil parish area in Hampshire, England, known for its high quality of life and largely rural character.
  • C. Good Hart
    Good Hart is a small unincorporated community and lakeside resort area on the shore of Lake Michigan in northern Michigan.
  • D. Hood
    "Hood" is a novel by Emma Donoghue that explores grief, identity, and a lesbian relationship in contemporary Ireland.
  • E. Hood
    Hood is a Marvel Comics supervillain and crime boss who uses mystical powers and underworld connections to challenge heroes and rival kingpins like Wilson Fisk.
  • 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_69d85a1794cc8190b0b428716296e63e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e04031e62c8190953b61207142af15 completed April 16, 2026, 1:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d4edee481908382ca5cd266f7b0 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:02 a.m.