Triple

T14889692
Position Surface form Disambiguated ID Type / Status
Subject Édouard Roche E359719 entity
Predicate workLocation P7 FINISHED
Object Montpellier E178364 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: Montpellier | Statement: [Édouard Roche, workLocation, Montpellier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montpellier
Context triple: [Édouard Roche, workLocation, Montpellier]
  • A. Montpellier chosen
    Montpellier is a major city in southern France known for its medieval old town, vibrant university life, and proximity to the Mediterranean coast.
  • B. Montpellier
    Montpellier is an affluent district of Cheltenham, England, known for its Regency architecture, boutique shops, and café culture.
  • C. Toulouse
    "Toulouse" is a popular 2011 electro house track by Dutch DJ and producer Nicky Romero that helped establish his international reputation in the EDM scene.
  • D. Toulouse
    Toulouse is a fictional orange kitten from Disney's animated film "The Aristocats," known for his playful, boisterous personality and admiration of alley cats.
  • E. Toulouse
    Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded5f6cf5c8190b6b28f58fafe5d59 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c2a938081909ccd9fe7c5021dc6 completed May 9, 2026, 3 p.m.
Created at: April 10, 2026, 2:09 a.m.