Triple

T17423996
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Pamiers E423688 entity
Predicate contains P35 FINISHED
Object Sainte-Suzanne
Sainte-Suzanne is a small French commune located in the Ariège department in the Occitanie region of southwestern France.
 E1267782 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: Sainte-Suzanne | Statement: [arrondissement of Pamiers, contains, Sainte-Suzanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sainte-Suzanne
Context triple: [arrondissement of Pamiers, contains, Sainte-Suzanne]
  • A. Sainte-Suzanne
    Sainte-Suzanne is a commune in northern Haiti known for its rural character and agricultural activities within the Nord-Est department.
  • B. Soussans
    Soussans is a wine-producing commune in the Médoc region of southwestern France, known for contributing vineyards to the prestigious Margaux appellation.
  • C. Saussignac
    Saussignac is a small wine-producing commune in southwestern France, known for its sweet white wines made primarily from Sémillon and other Bordeaux grape varieties.
  • D. Souvigny
    Souvigny is a historic town in central France known for its important Cluniac priory and medieval religious heritage.
  • E. Assencières
    Assencières is a small commune in the Aube department of north-central France.
  • 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: Sainte-Suzanne
Triple: [arrondissement of Pamiers, contains, Sainte-Suzanne]
Generated description
Sainte-Suzanne is a small French commune located in the Ariège department in the Occitanie region of southwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sainte-Suzanne
Target entity description: Sainte-Suzanne is a small French commune located in the Ariège department in the Occitanie region of southwestern France.
  • A. Sainte-Suzanne
    Sainte-Suzanne is a commune in northern Haiti known for its rural character and agricultural activities within the Nord-Est department.
  • B. Soussans
    Soussans is a wine-producing commune in the Médoc region of southwestern France, known for contributing vineyards to the prestigious Margaux appellation.
  • C. Saussignac
    Saussignac is a small wine-producing commune in southwestern France, known for its sweet white wines made primarily from Sémillon and other Bordeaux grape varieties.
  • D. Souvigny
    Souvigny is a historic town in central France known for its important Cluniac priory and medieval religious heritage.
  • E. Assencières
    Assencières is a small commune in the Aube department of north-central France.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4423999ac81909fdbd8bcffcb30c9 completed April 19, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01a80670bc8190aa8c7651e8973bb3 completed May 11, 2026, 9:57 a.m.
NEDg Description generation batch_6a01aa8b777c81909b8a4a5e790634e8 completed May 11, 2026, 10:08 a.m.
NED2 Entity disambiguation (via description) batch_6a01ab5a7a408190a457ddef4a0a7b09 completed May 11, 2026, 10:11 a.m.
Created at: April 10, 2026, 5:46 a.m.