Triple

T2781611
Position Surface form Disambiguated ID Type / Status
Subject Montpellier HSC E61708 entity
Predicate homeStadiumLocation P5282 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: [Montpellier HSC, homeStadiumLocation, Montpellier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montpellier
Context triple: [Montpellier HSC, homeStadiumLocation, 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. Toulouse
    Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
  • C. Rodez
    Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
  • D. Béziers
    Béziers is a historic city in southern France known for its wine production, ancient Roman heritage, and the famous Feria de Béziers festival.
  • E. Albi
    Albi is a historic city in southern France renowned for its red-brick medieval architecture and the UNESCO-listed Episcopal City centered around Sainte-Cécile Cathedral.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd9b88888190ab021afbaf3aa3c0 completed March 7, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69b54c16c05481908f451b492ca9f47f completed March 14, 2026, 11:52 a.m.
Created at: March 6, 2026, 9:57 p.m.