Triple

T10721453
Position Surface form Disambiguated ID Type / Status
Subject Wendy Greene Bricmont E252830 entity
Predicate hasFamilyName P18 FINISHED
Object Bricmont
Bricmont is a surname most notably associated with American film editor Wendy Greene Bricmont.
 E882140 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: Bricmont | Statement: [Wendy Greene Bricmont, hasFamilyName, Bricmont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bricmont
Context triple: [Wendy Greene Bricmont, hasFamilyName, Bricmont]
  • A. Stoumont
    Stoumont is a rural municipality in the province of Liège in eastern Belgium, known for its Ardennes landscapes and World War II Battle of the Bulge history.
  • B. Kaiserswerth
    Kaiserswerth is a historic district in northern Düsseldorf, Germany, known for its medieval castle ruins and picturesque old town along the Rhine River.
  • C. Moensberg
    Moensberg is a residential neighborhood in the municipality of Uccle in the Brussels-Capital Region of Belgium.
  • D. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • E. Heverlee
    Heverlee is a suburb of Leuven in the Flemish Brabant province of Belgium, known for its residential areas, green spaces, and nearby university facilities.
  • 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: Bricmont
Triple: [Wendy Greene Bricmont, hasFamilyName, Bricmont]
Generated description
Bricmont is a surname most notably associated with American film editor Wendy Greene Bricmont.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bricmont
Target entity description: Bricmont is a surname most notably associated with American film editor Wendy Greene Bricmont.
  • A. Stoumont
    Stoumont is a rural municipality in the province of Liège in eastern Belgium, known for its Ardennes landscapes and World War II Battle of the Bulge history.
  • B. Kaiserswerth
    Kaiserswerth is a historic district in northern Düsseldorf, Germany, known for its medieval castle ruins and picturesque old town along the Rhine River.
  • C. Moensberg
    Moensberg is a residential neighborhood in the municipality of Uccle in the Brussels-Capital Region of Belgium.
  • D. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • E. Heverlee
    Heverlee is a suburb of Leuven in the Flemish Brabant province of Belgium, known for its residential areas, green spaces, and nearby university facilities.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70d43655081909b071100c96cb4f6 completed April 9, 2026, 2:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbb72b9ce08190a9134f3365d3f8cb completed April 12, 2026, 3:15 p.m.
NEDg Description generation batch_69dbbbe545748190b2bdbc3a75224eb0 completed April 12, 2026, 3:36 p.m.
NED2 Entity disambiguation (via description) batch_69dbc59b315081909362892f5b989d25 completed April 12, 2026, 4:17 p.m.
Created at: April 8, 2026, 9:13 p.m.