Triple

T17107347
Position Surface form Disambiguated ID Type / Status
Subject municipality of Hellendoorn E415134 entity
Predicate hasVillage P4011 FINISHED
Object Haarle E1248536 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: Haarle | Statement: [municipality of Hellendoorn, hasVillage, Haarle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haarle
Context triple: [municipality of Hellendoorn, hasVillage, Haarle]
  • A. Haarle chosen
    Haarle is a small village in the Dutch province of Overijssel, situated within the municipality of Hellendoorn.
  • B. Hulst
    Hulst is a historic fortified town and municipality in the Dutch province of Zeeland, near the border with Belgium.
  • C. Haaksbergen
    Haaksbergen is a town in the eastern Netherlands, near the German border, known for its rural surroundings and cross-border ties with neighboring German communities.
  • D. Hansweert
    Hansweert is a small village in the Dutch province of Zeeland, known historically as a canal and shipping hub along the Western Scheldt.
  • E. Holendrecht
    Holendrecht is a metro station in Amsterdam serving the southeastern part of the city, including the nearby academic hospital and university campus.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc280b0c8190b9e620b90e0d4b40 completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a019540819083ce6100b24f8cfb completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:35 a.m.