Triple

T16020636
Position Surface form Disambiguated ID Type / Status
Subject Cèze E388587 entity
Predicate flowsThrough P225 FINISHED
Object Bessèges
Bessèges is a commune in the Gard department of southern France, historically known for its coal mining and location in the Cévennes region.
E1196248 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: Bessèges | Statement: [Cèze, flowsThrough, Bessèges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bessèges
Context triple: [Cèze, flowsThrough, Bessèges]
  • A. Bédarieux
    Bédarieux is a commune in southern France’s Hérault department, known for its location in the Orb valley at the foothills of the Massif Central.
  • B. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • C. Olliergues
    Olliergues is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • D. Assencières
    Assencières is a small commune in the Aube department of north-central France.
  • E. Serques
    Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
  • 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: Bessèges
Triple: [Cèze, flowsThrough, Bessèges]
Generated description
Bessèges is a commune in the Gard department of southern France, historically known for its coal mining and location in the Cévennes region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bessèges
Target entity description: Bessèges is a commune in the Gard department of southern France, historically known for its coal mining and location in the Cévennes region.
  • A. Bédarieux
    Bédarieux is a commune in southern France’s Hérault department, known for its location in the Orb valley at the foothills of the Massif Central.
  • B. Aiguillon
    Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
  • C. Olliergues
    Olliergues is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • D. Assencières
    Assencières is a small commune in the Aube department of north-central France.
  • E. Serques
    Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183231f2c81908f4e4037c3aa180b completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff295a0e08190b80d363f0a48094a completed May 10, 2026, 2:51 a.m.
NEDg Description generation batch_69fff35ded288190b4d261358f1661cb completed May 10, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69fff3f2760c8190a58fedc2798614ae completed May 10, 2026, 2:56 a.m.
Created at: April 10, 2026, 4:55 a.m.