Triple

T3526706
Position Surface form Disambiguated ID Type / Status
Subject Maurice Maeterlinck E74556 entity
Predicate givenName P17 FINISHED
Object Maurice E44841 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: Maurice | Statement: [Maurice Maeterlinck, givenName, Maurice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maurice
Context triple: [Maurice Maeterlinck, givenName, Maurice]
  • A. Maurice chosen
    Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
  • B. Maurice
    Maurice is a 1987 British romantic drama film, based on E.M. Forster’s novel, that explores same-sex love and class in early 20th-century England.
  • C. Marcel
    Marcel is a masculine given name of French origin, commonly used in various European countries.
  • D. Swann
    Swann is a surname most prominently associated with Lynn Swann, a Hall of Fame American football wide receiver and former politician.
  • E. Monsieur
    Monsieur was the traditional honorific title used at the French court for Philippe I, Duke of Orléans, the younger brother of King Louis XIV.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6bb0748190bfccfe25d2ab41b7 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e90e67c81909944bb81d89e039b completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.