Triple

T425846
Position Surface form Disambiguated ID Type / Status
Subject Ardennes Forest E9605 entity
Predicate partOf P40 FINISHED
Object Ardennes E9605 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: Ardennes | Statement: [Ardennes Forest, partOf, Ardennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ardennes
Context triple: [Ardennes Forest, partOf, Ardennes]
  • A. Ardennes Forest chosen
    The Ardennes Forest is a densely wooded, hilly region in Belgium, Luxembourg, and France that became historically significant as a key invasion route used by German forces in both World Wars.
  • B. Houffalize
    Houffalize is a small town in the Belgian Ardennes known for its World War II history, outdoor tourism, and scenic natural surroundings.
  • C. Alsace
    Alsace is a historical and cultural region in northeastern France known for its blend of French and German influences, picturesque villages, and renowned wines.
  • D. Weser Uplands
    The Weser Uplands is a hilly, forested region in central Germany known for its picturesque landscapes, traditional half-timbered towns, and association with many of the Brothers Grimm fairy tales.
  • E. Black Forest
    The Black Forest is a large, densely wooded mountain range in southwestern Germany known for its picturesque villages, cuckoo clocks, and origin of the Danube River.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2eed56ab481909eec289075496260 completed Feb. 28, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69a42a187e208190ba58c0d9f68aaef8 completed March 1, 2026, 11:59 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.