Triple

T10984063
Position Surface form Disambiguated ID Type / Status
Subject Reitdiep E259581 entity
Predicate hasSettlementOnBank P1010 FINISHED
Object Dorkwerd E526532 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: Dorkwerd | Statement: [Reitdiep, hasSettlementOnBank, Dorkwerd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dorkwerd
Context triple: [Reitdiep, hasSettlementOnBank, Dorkwerd]
  • A. Uithoorn
    Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
  • B. Beinsdorp
    Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
  • C. Oosterwijtwerd chosen
    Oosterwijtwerd is a small village in the province of Groningen in the northern Netherlands, known for its rural character and historic church.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d772ec55fc81909b2b15f2493dddc6 completed April 9, 2026, 9:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69f671788ec88190852df74698bc4518 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:24 p.m.