Triple

T10240838
Position Surface form Disambiguated ID Type / Status
Subject Karl Krafft E243584 entity
Predicate residence P75 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: [Karl Krafft, residence, Alsace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsace
Context triple: [Karl Krafft, residence, 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d21e27f08190b956d351a75c7c52 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f780c7808190993e7c37cb4d18a3 completed April 9, 2026, 12:49 a.m.
Created at: April 6, 2026, 11:24 a.m.