Triple

T6746117
Position Surface form Disambiguated ID Type / Status
Subject Arlon E154217 entity
Predicate historicalRegion P915 FINISHED
Object Gaume
Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
 E620419 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: Gaume | Statement: [Arlon, historicalRegion, Gaume]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gaume
Context triple: [Arlon, historicalRegion, Gaume]
  • A. Garmes
    Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
  • B. Gamay
    Gamay is a red wine grape variety best known for producing light, fruity wines, particularly in France’s Beaujolais region.
  • C. Gamay
    Gamay is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and fishing- and agriculture-based local economy.
  • D. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • E. Valleiry
    Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
  • 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: Gaume
Triple: [Arlon, historicalRegion, Gaume]
Generated description
Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gaume
Target entity description: Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
  • A. Garmes
    Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
  • B. Gamay
    Gamay is a red wine grape variety best known for producing light, fruity wines, particularly in France’s Beaujolais region.
  • C. Gamay
    Gamay is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and fishing- and agriculture-based local economy.
  • D. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • E. Valleiry
    Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
  • 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_69c6880ef37881909268a5a7299b9293 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1b8a0f0819086b802983e8ffcb6 completed March 27, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a76f0c8819097e19e016988f0b4 completed March 28, 2026, 12:01 a.m.
NEDg Description generation batch_69c71d2b9f748190bfa4438b47aef820 completed March 28, 2026, 12:13 a.m.
NED2 Entity disambiguation (via description) batch_69c71da5ef54819099250aca55b1b27f completed March 28, 2026, 12:15 a.m.
Created at: March 27, 2026, 2:10 p.m.