Triple

T4301192
Position Surface form Disambiguated ID Type / Status
Subject Hautes-Pyrénées E99839 entity
Predicate subprefecture P9697 FINISHED
Object Bagnères-de-Bigorre E152412 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: Bagnères-de-Bigorre | Statement: [Hautes-Pyrénées, subprefecture, Bagnères-de-Bigorre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bagnères-de-Bigorre
Context triple: [Hautes-Pyrénées, subprefecture, Bagnères-de-Bigorre]
  • A. Bagnères-de-Bigorre chosen
    Bagnères-de-Bigorre is a spa and ski resort town in the French Pyrenees, known for its thermal baths and mountain tourism.
  • B. Argelès-Gazost
    Argelès-Gazost is a small spa and tourist town in southwestern France, nestled in the Pyrenees and serving as a gateway to nearby mountain valleys and national parks.
  • C. Mazamet
    Mazamet is a town in southern France known historically for its wool and leather industries, situated in the Tarn department within the Occitanie region.
  • D. Tarbes
    Tarbes is a historic city in southwestern France, serving as the capital of the Hautes-Pyrénées department at the foot of the Pyrenees.
  • E. Manosque
    Manosque is a historic town in southeastern France’s Provence region, known for its medieval old town, surrounding lavender fields, and proximity to the Luberon mountains.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509fb2b88190a13ab88a5b924052 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0774d388190aaff15f528fe1bc2 completed March 14, 2026, 9:17 p.m.
Created at: March 12, 2026, 11:08 p.m.