Triple

T12580430
Position Surface form Disambiguated ID Type / Status
Subject Margot Frank E300320 entity
Predicate givenName P17 FINISHED
Object Margot E300320 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: Margot | Statement: [Margot Frank, givenName, Margot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margot
Context triple: [Margot Frank, givenName, Margot]
  • A. Margot
    Margot is the introspective, conflicted protagonist of the Canadian romantic drama film "Take This Waltz," whose emotional journey explores the complexities of love, desire, and long-term relationships.
  • B. Margot chosen
    Margot is a feminine given name of French origin, often associated with Margot Frank, the elder sister of diarist Anne Frank.
  • C. Margot Wendice
    Margot Wendice is the wealthy wife targeted in her husband's elaborate murder plot in Alfred Hitchcock's thriller "Dial M for Murder."
  • D. Margot Verger
    Margot Verger is a character in Thomas Harris's Hannibal universe, depicted as the abused, bodybuilding sister of sadistic millionaire Mason Verger.
  • E. Mélanie
    Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954b867dc8190af8a70f797e4d133 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684d8b8d081908f271e75e6472914 completed May 2, 2026, 11:12 p.m.
Created at: April 9, 2026, 5:01 p.m.