Triple

T10619325
Position Surface form Disambiguated ID Type / Status
Subject Malmedy E295666 entity
Predicate near P350 FINISHED
Object Baugnez
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.
 E877032 NE FINISHED

How this triple was built (4 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: [Malmedy, near, Baugnez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Baugnez
Context triple: [Malmedy, near, Baugnez]
  • A. Debourg
    Debourg is a tram terminus and transport hub in Lyon, France, serving as one end of the city’s T1 tram line.
  • B. Bertogne
    Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
  • C. Bongrand
    Bongrand is a fictional character in Émile Zola’s novel *L’Œuvre*, depicted as an older, established painter who contrasts with the avant-garde ambitions of the protagonist.
  • D. Boignée
    Boignée is a village that forms one of the municipal sections of the municipality of Sombreffe in the province of Namur, Wallonia, Belgium.
  • E. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Baugnez
Triple: [Malmedy, near, Baugnez]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Baugnez
Target entity description: 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.
  • A. Debourg
    Debourg is a tram terminus and transport hub in Lyon, France, serving as one end of the city’s T1 tram line.
  • B. Bertogne
    Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
  • C. Bongrand
    Bongrand is a fictional character in Émile Zola’s novel *L’Œuvre*, depicted as an older, established painter who contrasts with the avant-garde ambitions of the protagonist.
  • D. Boignée
    Boignée is a village that forms one of the municipal sections of the municipality of Sombreffe in the province of Namur, Wallonia, Belgium.
  • E. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • F. None of above. chosen

Provenance (5 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d6df6ee1848190a7d5fcd40b06cfe3 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a2c8a048190b9a62f1c68ac217a completed April 10, 2026, 10:31 p.m.
NEDg Description generation batch_69d97cc07100819088683a0d79b2baa0 completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e015b088190a97822675eecaa5a completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 8:21 p.m.