Triple

T7543112
Position Surface form Disambiguated ID Type / Status
Subject Alsace campaign E178329 entity
Predicate location 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: [Alsace campaign, location, Alsace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsace
Context triple: [Alsace campaign, location, 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. Alsacia
    Alsacia is a Madrid Metro station on Line 2 serving the San Blas-Canillejas district in eastern Madrid, Spain.
  • C. 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.
  • D. French Lorraine
    French Lorraine is a historical region in northeastern France whose culture reflects a blend of French and Germanic influences.
  • E. 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.
  • 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8762b048190a0b262f9cb3fe1b0 completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856b93188819080c769a2a1b122f4 completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:48 p.m.