Triple

T5083176
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam Metro line 50 E114571 entity
Predicate hasStation P35 FINISHED
Object Holendrecht E282001 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: Holendrecht | Statement: [Amsterdam Metro line 50, hasStation, Holendrecht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holendrecht
Context triple: [Amsterdam Metro line 50, hasStation, Holendrecht]
  • A. Holendrecht chosen
    Holendrecht is a metro station in Amsterdam serving the southeastern part of the city, including the nearby academic hospital and university campus.
  • B. Vollenhove
    Vollenhove is a historic town in the Dutch province of Overijssel, known for its former status as a regional administrative and noble center with several notable estates and churches.
  • C. Hansweert
    Hansweert is a small village in the Dutch province of Zeeland, known historically as a canal and shipping hub along the Western Scheldt.
  • D. Nijverdal
    Nijverdal is a town in the Dutch province of Overijssel known as a gateway to the Sallandse Heuvelrug National Park and its surrounding natural landscapes.
  • E. Leusden
    Leusden is a Dutch town and municipality in the central Netherlands, known for its green residential character and proximity to the city of Amersfoort.
  • 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_69bd443dbf908190a9401e9c2dc7bd7d completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7517af308190bab5507a9344bf68 completed March 20, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6847ad9fc819085b0d6c886488c3b completed April 20, 2026, 7:54 p.m.
Created at: March 20, 2026, 1:39 p.m.