Triple

T3014996
Position Surface form Disambiguated ID Type / Status
Subject Remoulins E82316 entity
Predicate hasRiver P165 FINISHED
Object Gardon
The Gardon is a river in southern France known for flowing through the Gard department and beneath the famous Pont du Gard Roman aqueduct.
 E317805 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: Gardon | Statement: [Remoulins, hasRiver, Gardon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gardon
Context triple: [Remoulins, hasRiver, Gardon]
  • A. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • B. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • C. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • D. Dugommier
    Dugommier was a French Revolutionary general noted for his leadership in key campaigns such as the Siege of Toulon and the War of the Pyrenees.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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: Gardon
Triple: [Remoulins, hasRiver, Gardon]
Generated description
The Gardon is a river in southern France known for flowing through the Gard department and beneath the famous Pont du Gard Roman aqueduct.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gardon
Target entity description: The Gardon is a river in southern France known for flowing through the Gard department and beneath the famous Pont du Gard Roman aqueduct.
  • A. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • B. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • C. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • D. Dugommier
    Dugommier was a French Revolutionary general noted for his leadership in key campaigns such as the Siege of Toulon and the War of the Pyrenees.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a69e8148190a97507740c9d26a8 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6b78448190beb41460314278ec completed March 11, 2026, 8:57 a.m.
NEDg Description generation batch_69b12faf75ac81909031430d58919c95 completed March 11, 2026, 9:02 a.m.
NED2 Entity disambiguation (via description) batch_69b1c7d3f2c88190aa26d8d12777b2a2 completed March 11, 2026, 7:51 p.m.
Created at: March 8, 2026, 3 p.m.