Triple

T27473794
Position Surface form Disambiguated ID Type / Status
Subject Sauldre basin E693394 entity
Predicate partOf P40 FINISHED
Object French river basins network
The French river basins network is a national hydrological system that organizes and manages France’s major river catchment areas for water resources, environmental protection, and regional planning.
 E1774374 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: French river basins network | Statement: [Sauldre basin, partOf, French river basins network]
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: French river basins network
Triple: [Sauldre basin, partOf, French river basins network]
Generated description
The French river basins network is a national hydrological system that organizes and manages France’s major river catchment areas for water resources, environmental protection, and regional planning.

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_69ef538105548190a771cc5a0cf8c211 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62e422e7c8190a256e3155a22ba27 completed May 2, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbe4fee081909618f6f3bf12a740 completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bc906eb481908d12f171b1230dbe completed May 24, 2026, 8:53 a.m.
NED2 Entity disambiguation (via description) batch_6a12bd3f12b481908606b8e373ff408a completed May 24, 2026, 8:56 a.m.
Created at: April 27, 2026, 12:55 p.m.