Triple

T37814793
Position Surface form Disambiguated ID Type / Status
Subject Wezep E942743 entity
Predicate hasSportsClub P346 FINISHED
Object Wezep Hattemerbroek Combinatie football club
Wezep Hattemerbroek Combinatie football club is a Dutch amateur football club representing the towns of Wezep and Hattemerbroek in the Netherlands.
E2243889 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: Wezep Hattemerbroek Combinatie football club | Statement: [Wezep, hasSportsClub, Wezep Hattemerbroek Combinatie football club]
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: Wezep Hattemerbroek Combinatie football club
Triple: [Wezep, hasSportsClub, Wezep Hattemerbroek Combinatie football club]
Generated description
Wezep Hattemerbroek Combinatie football club is a Dutch amateur football club representing the towns of Wezep and Hattemerbroek in the Netherlands.

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_69f76ee987588190906506e759be5db3 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb1a0987881909b19430eae8beb7b completed May 6, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40f195f5c48190808b31e6c9370dfe completed June 28, 2026, 10:04 a.m.
NEDg Description generation batch_6a40f23ecbc081909576b02690c2cc92 completed June 28, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a40f2defa148190a773cdebe781a243 completed June 28, 2026, 10:09 a.m.
Created at: May 3, 2026, 4:19 p.m.