Triple

T4235939
Position Surface form Disambiguated ID Type / Status
Subject Lac de Pareloup E94691 entity
Predicate inflow P415 FINISHED
Object Bage
Bage is a river in southern France that serves as one of the main tributaries feeding the Lac de Pareloup reservoir.
 E423701 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: Bage | Statement: [Lac de Pareloup, inflow, Bage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bage
Context triple: [Lac de Pareloup, inflow, Bage]
  • A. Bages
    Bages is a central comarca (county) in Catalonia, Spain, known for its historic town of Manresa and its mix of industrial, agricultural, and natural landscapes.
  • B. Barkot
    Barkot is a small town in Uttarkashi district of Uttarakhand, India, that serves as an important stopover and base for pilgrims traveling to the Yamunotri temple in the Garhwal Himalayas.
  • C. Bago
    Bago is a component city in the province of Negros Occidental in the Philippines, known for its agricultural economy and historical significance.
  • D. Baflo
    Baflo is a village in the Dutch province of Groningen, known for its historic church and rural character.
  • E. Bekwarra
    Bekwarra is a notable town and local government area in southeastern Nigeria, recognized for its predominantly agrarian community and cultural heritage within Cross River State.
  • 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: Bage
Triple: [Lac de Pareloup, inflow, Bage]
Generated description
Bage is a river in southern France that serves as one of the main tributaries feeding the Lac de Pareloup reservoir.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bage
Target entity description: Bage is a river in southern France that serves as one of the main tributaries feeding the Lac de Pareloup reservoir.
  • A. Bages
    Bages is a central comarca (county) in Catalonia, Spain, known for its historic town of Manresa and its mix of industrial, agricultural, and natural landscapes.
  • B. Barkot
    Barkot is a small town in Uttarkashi district of Uttarakhand, India, that serves as an important stopover and base for pilgrims traveling to the Yamunotri temple in the Garhwal Himalayas.
  • C. Bago
    Bago is a component city in the province of Negros Occidental in the Philippines, known for its agricultural economy and historical significance.
  • D. Baflo
    Baflo is a village in the Dutch province of Groningen, known for its historic church and rural character.
  • E. Bekwarra
    Bekwarra is a notable town and local government area in southeastern Nigeria, recognized for its predominantly agrarian community and cultural heritage within Cross River State.
  • 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_69b34537cc6481909cd0a96acbb33ef7 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e72ff588190a50c04ab975612dd completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a866c2448190aaed83d8da3669b8 completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a8f374fc8190830286dfadc9bdbb completed March 14, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69b5a99a4a9c8190a7e9bbc119d8d775 completed March 14, 2026, 6:31 p.m.
Created at: March 12, 2026, 11:05 p.m.