Triple

T19620757
Position Surface form Disambiguated ID Type / Status
Subject Battle of Baugnez E470999 entity
Predicate location P40 FINISHED
Object Baugnez NE NERFINISHED

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: Baugnez | Statement: [Battle of Baugnez, location, Baugnez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baugnez
Context triple: [Battle of Baugnez, location, Baugnez]
  • A. Baugnez chosen
    Baugnez is a small hamlet in eastern Belgium best known as the site of the World War II Malmedy massacre during the Battle of the Bulge.
  • B. Dagneux
    Dagneux is a commune in eastern France’s Ain department, known for its residential character and proximity to the Lyon metropolitan area.
  • C. Debourg
    Debourg is a tram terminus and transport hub in Lyon, France, serving as one end of the city’s T1 tram line.
  • D. Bertogne
    Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
  • E. Seytroux
    Seytroux is a small mountain village and commune in the Haute-Savoie department of southeastern France, situated in the Chablais region of the French Alps.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640e512d08190a76bf81b3282e0e5 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:43 p.m.