Triple

T6942166
Position Surface form Disambiguated ID Type / Status
Subject Loire (department) E160703 entity
Predicate hasMajorCity P316 FINISHED
Object Roanne E96070 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: Roanne | Statement: [Loire (department), hasMajorCity, Roanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roanne
Context triple: [Loire (department), hasMajorCity, Roanne]
  • A. Roanne chosen
    Roanne is a commune and industrial town in central France, situated on the Loire River and known historically for its textile industry and river port.
  • B. Tournus
    Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
  • C. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • D. Compiegne
    Compiègne is a historic city in northern France known for its royal château, forest, and role in significant events such as the signing of the 1918 Armistice.
  • E. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • 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_69c6884f3db4819080ad65da69386206 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da85f43881909549ac26b3db135a completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769fa17748190a1ca72ca86cce827 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:28 p.m.