Triple

T35290258
Position Surface form Disambiguated ID Type / Status
Subject Waverveen E1019200 entity
Predicate hasNearbyWaterBody P1489 FINISHED
Object Waver river
The Waver river is a small waterway in the province of Utrecht in the Netherlands, flowing through the rural area around Waverveen and contributing to its characteristic polder landscape.
E2297014 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: Waver river | Statement: [Waverveen, hasNearbyWaterBody, Waver 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: Waver river
Triple: [Waverveen, hasNearbyWaterBody, Waver river]
Generated description
The Waver river is a small waterway in the province of Utrecht in the Netherlands, flowing through the rural area around Waverveen and contributing to its characteristic polder landscape.

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_69f76de7eedc8190a3bdc64ebbc05b42 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f79012e2e481908c587ff189b3deb3 completed May 3, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82f46818f08190bcbce3c45be4422b completed Aug. 17, 2026, 11:45 a.m.
NEDg Description generation batch_6a82f4e6f8a88190b76d9ae821715261 completed Aug. 17, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_6a82f53d16b88190bf3f9aa99b23039e completed Aug. 17, 2026, 11:49 a.m.
Created at: May 3, 2026, 4:03 p.m.