Triple

T3953992
Position Surface form Disambiguated ID Type / Status
Subject Var E84932 entity
Predicate hasSubprefecture P9697 FINISHED
Object Draguignan E312999 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: Draguignan | Statement: [Var, hasSubprefecture, Draguignan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Draguignan
Context triple: [Var, hasSubprefecture, Draguignan]
  • A. Draguignan chosen
    Draguignan is a town in southeastern France’s Var department, known as a former prefecture and gateway to the Provence region.
  • B. 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.
  • C. Gradignan
    Gradignan is a suburban commune in southwestern France’s Gironde department, forming part of the Bordeaux metropolitan area and known for its green spaces and wine-growing surroundings.
  • D. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • E. Frontignan
    Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef93b8f5c8190bdb062a76b68b3e0 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b67b9e1b4081909f53466a603d7061 completed March 15, 2026, 9:27 a.m.
Created at: March 9, 2026, 3:30 p.m.