Triple

T30701707
Position Surface form Disambiguated ID Type / Status
Subject Anet E781626 entity
Predicate locatedOn P40 FINISHED
Object river Eure
The river Eure is a tributary of the Seine in northern France, flowing through the regions of Normandy and Centre-Val de Loire and passing towns such as Chartres and Évreux.
 E1926781 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: river Eure | Statement: [Anet, locatedOn, river Eure]
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: river Eure
Triple: [Anet, locatedOn, river Eure]
Generated description
The river Eure is a tributary of the Seine in northern France, flowing through the regions of Normandy and Centre-Val de Loire and passing towns such as Chartres and Évreux.

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_69f224abfcf081909492e64d3cc35262 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68bdf2b3c81909578a19e0190e45d completed May 2, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28711844408190946b2d573fe6440e completed June 9, 2026, 8:01 p.m.
NEDg Description generation batch_6a287689fc648190a3ccf1b5c94a40ad completed June 9, 2026, 8:24 p.m.
NED2 Entity disambiguation (via description) batch_6a28770182548190b06963ca19108cb8 completed June 9, 2026, 8:26 p.m.
Created at: April 29, 2026, 8:34 p.m.