Triple

T35999115
Position Surface form Disambiguated ID Type / Status
Subject Durance River canal system E1041078 entity
Predicate component P35 FINISHED
Object Canal de Craponne
The Canal de Craponne is a historic irrigation canal in southern France that diverted water from the Durance River to transform the arid Crau plain into fertile agricultural land.
E2169282 NE FINISHED

How this triple was built (2 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: Canal de Craponne | Statement: [Durance River canal system, component, Canal de Craponne]
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: Canal de Craponne
Triple: [Durance River canal system, component, Canal de Craponne]
Generated description
The Canal de Craponne is a historic irrigation canal in southern France that diverted water from the Durance River to transform the arid Crau plain into fertile agricultural land.

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_69f76e29084c819083987b828d414de7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac8118148190bef390a078185205 completed May 3, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ddf0ed74819097d9b5b75c347895 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38de652e14819096a312b01caea5fe completed June 22, 2026, 7:04 a.m.
NED2 Entity disambiguation (via description) batch_6a38dec27c5c8190822a585f2af6ef26 completed June 22, 2026, 7:05 a.m.
Created at: May 3, 2026, 4:07 p.m.