Triple

T17824710
Position Surface form Disambiguated ID Type / Status
Subject Dyle River E445083 entity
Predicate confluenceWith P2416 FINISHED
Object Nete River
The Nete River is a waterway in northern Belgium that flows through the province of Antwerp and ultimately contributes to the Scheldt river system.
 E2074332 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: Nete River | Statement: [Dyle River, confluenceWith, Nete River]
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: Nete River
Triple: [Dyle River, confluenceWith, Nete River]
Generated description
The Nete River is a waterway in northern Belgium that flows through the province of Antwerp and ultimately contributes to the Scheldt river system.

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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4891352ac8190ad3d669fea1c9fbb completed April 19, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3689ad316081908599ae98505b8698 completed June 20, 2026, 12:38 p.m.
NEDg Description generation batch_6a368a465dec8190abfed840dfbf11e9 completed June 20, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_6a368ac9af4c81909847e2aedf58afae completed June 20, 2026, 12:42 p.m.
Created at: April 10, 2026, 10:15 a.m.