Triple

T2026908
Position Surface form Disambiguated ID Type / Status
Subject Colmar E44428 entity
Predicate locatedIn P40 FINISHED
Object Alsace E19573 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: Alsace | Statement: [Colmar, locatedIn, Alsace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsace
Context triple: [Colmar, locatedIn, Alsace]
  • A. Alsace chosen
    Alsace is a historical and cultural region in northeastern France known for its blend of French and German influences, picturesque villages, and renowned wines.
  • B. Alsace-Lorraine
    Alsace-Lorraine is a historically contested border region between France and Germany, known for its mixed cultural heritage and strategic importance in European conflicts.
  • C. Franche-Comté
    Franche-Comté is a historical region in eastern France bordering Switzerland, known for its mountainous Jura landscapes, distinctive cheeses like Comté, and a past marked by shifting control between France and the Habsburgs.
  • D. Bas-Rhin
    Bas-Rhin is a department in the Grand Est region of northeastern France, known for its border with Germany and its capital, the European institutional city of Strasbourg.
  • E. Meurthe-et-Moselle
    Meurthe-et-Moselle is a department in northeastern France known for its capital Nancy, rich industrial history, and Art Nouveau architectural heritage.
  • 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_69a889144f2481909932f0746a93023d completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb91055d88190a980e7b42e5895d4 completed March 7, 2026, 5:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae517e7c2481909d2840a734eed96b completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:38 p.m.