Triple

T14147227
Position Surface form Disambiguated ID Type / Status
Subject Ville Haute E350581 entity
Predicate hasViewOf P854 FINISHED
Object Alzette valley E569988 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: Alzette valley | Statement: [Ville Haute, hasViewOf, Alzette valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alzette valley
Context triple: [Ville Haute, hasViewOf, Alzette valley]
  • A. Alzette chosen
    The Alzette is a river in Luxembourg and France that flows through Luxembourg City and ultimately joins the Sauer, making it an important waterway in the region.
  • B. Rodange
    Rodange is a town in southwestern Luxembourg known as an important railway junction near the Belgian and French borders.
  • C. Aubenas
    Aubenas is a historic market town in southern France known for its medieval castle and role as a commercial center of the Ardèche region.
  • D. Blegny
    Blegny is a municipality in eastern Belgium known for its historic coal mining heritage and rural character.
  • E. Lantheuil
    Lantheuil is a small commune in the Calvados department of the Normandy region in northwestern France.
  • 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_69d827865f608190b311820428ae027b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de612266248190a8591b646fe30ae6 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf1d8c448190bd223258b28fecc9 completed May 7, 2026, 6:51 p.m.
Created at: April 10, 2026, 12:54 a.m.