Triple

T4734333
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 308 E105086 entity
Predicate assemblyLocation P40 FINISHED
Object Mulhouse, France E78039 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: Mulhouse, France | Statement: [Peugeot 308, assemblyLocation, Mulhouse, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mulhouse, France
Context triple: [Peugeot 308, assemblyLocation, Mulhouse, France]
  • A. Mulhouse chosen
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • B. Ribemont, France
    Ribemont, France is a small commune in northern France best known as the birthplace of Enlightenment philosopher and mathematician Marquis de Condorcet.
  • C. Sochaux, France
    Sochaux, France is an industrial town in eastern France best known as the historic home of the Peugeot automobile manufacturing complex.
  • D. Auxerre, France
    Auxerre, France is a historic city in the Burgundy region known for its medieval architecture, Gothic cathedral, and role as a cultural and economic center along the Yonne River.
  • E. Montreuil, France
    Montreuil is a suburban commune in the eastern part of the Paris metropolitan area, known for its diverse population and mix of residential, commercial, and cultural spaces.
  • 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_69bd43ee52048190b81a4f066534ffb3 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6467a1fc819089485b4d76e0edc4 completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a0fc0b88190a1eb07f6fb021b86 completed March 21, 2026, 6:26 a.m.
Created at: March 20, 2026, 1:19 p.m.