Triple

T27309021
Position Surface form Disambiguated ID Type / Status
Subject Steenbergen E689148 entity
Predicate locatedNearWaterBody P25960 FINISHED
Object Steenbergse Vliet
Steenbergse Vliet is a waterway in the Dutch province of North Brabant that flows near the town of Steenbergen and forms part of the local river and canal network.
E1890109 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: Steenbergse Vliet | Statement: [Steenbergen, locatedNearWaterBody, Steenbergse Vliet]
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: Steenbergse Vliet
Triple: [Steenbergen, locatedNearWaterBody, Steenbergse Vliet]
Generated description
Steenbergse Vliet is a waterway in the Dutch province of North Brabant that flows near the town of Steenbergen and forms part of the local river and canal network.

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_69ef355b931c8190a63cafaf7bcc008b completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627b1835481909b0e68123b14f96b completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26f19da1248190920241946886d4d9 completed June 8, 2026, 4:45 p.m.
NEDg Description generation batch_6a26f33040c8819089f7529dc0b89c6e completed June 8, 2026, 4:52 p.m.
NED2 Entity disambiguation (via description) batch_6a26f400153481909afc16df890350c1 completed June 8, 2026, 4:55 p.m.
Created at: April 27, 2026, 11:26 a.m.