Triple

T17252569
Position Surface form Disambiguated ID Type / Status
Subject Dane Clark E418791 entity
Predicate spouse P13 FINISHED
Object Margo E282085 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: Margo | Statement: [Dane Clark, spouse, Margo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margo
Context triple: [Dane Clark, spouse, Margo]
  • A. Margo
    Margo is the responsible and intelligent eldest of Gru’s three adopted daughters in the Despicable Me franchise.
  • B. Margo
    Margo is a feminine given name commonly used in English-speaking countries, often considered a variant of Margot or Margaret.
  • C. Margo chosen
    Margo was a Mexican-American actress and dancer known for her work in Hollywood films of the 1930s and 1940s and for her later stage and television appearances.
  • D. Marnie
    Marnie is the given name of Darcey Bussell, the renowned British ballerina and former principal dancer of The Royal Ballet.
  • E. Marnie
    Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e6a1b648190a8bb2deb67bbdfdc completed April 19, 2026, 1:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170fb89248190ae431ce51dfeaffd completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.