Triple

T1443351
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam Metro line 53 E31122 entity
Predicate hasStation P35 FINISHED
Object Strandvliet
Strandvliet is a metro station in Amsterdam that serves passengers on the city's rapid transit network.
 E241015 NE FINISHED

How this triple was built (4 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: Strandvliet | Statement: [Amsterdam Metro line 53, hasStation, Strandvliet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Strandvliet
Context triple: [Amsterdam Metro line 53, hasStation, Strandvliet]
  • A. Geervliet
    Geervliet is a small historic town in the western Netherlands, located in the province of South Holland.
  • B. Zwartewaal
    Zwartewaal is a small village in the western Netherlands, located in the province of South Holland.
  • C. IJmeer
    IJmeer is a shallow lake in the Netherlands, located east of Amsterdam and forming part of the IJsselmeer lake system.
  • D. Werkendam
    Werkendam is a town in the Dutch province of North Brabant, known as a gateway to the Biesbosch National Park and its riverine landscapes.
  • E. Spaarne
    Spaarne is a river in the province of North Holland in the Netherlands that flows through the historic city of Haarlem.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Strandvliet
Triple: [Amsterdam Metro line 53, hasStation, Strandvliet]
Generated description
Strandvliet is a metro station in Amsterdam that serves passengers on the city's rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Strandvliet
Target entity description: Strandvliet is a metro station in Amsterdam that serves passengers on the city's rapid transit network.
  • A. Geervliet
    Geervliet is a small historic town in the western Netherlands, located in the province of South Holland.
  • B. Zwartewaal
    Zwartewaal is a small village in the western Netherlands, located in the province of South Holland.
  • C. IJmeer
    IJmeer is a shallow lake in the Netherlands, located east of Amsterdam and forming part of the IJsselmeer lake system.
  • D. Werkendam
    Werkendam is a town in the Dutch province of North Brabant, known as a gateway to the Biesbosch National Park and its riverine landscapes.
  • E. Spaarne
    Spaarne is a river in the province of North Holland in the Netherlands that flows through the historic city of Haarlem.
  • F. None of above. chosen

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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c533a158819084d0917776edb6e5 completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d78933c81908359b0010b9e6147 completed March 9, 2026, 5:41 a.m.
NEDg Description generation batch_69ae5dd76d408190ab324280344c7b79 completed March 9, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69ae5e4bfda88190af66dcb564c1e731 completed March 9, 2026, 5:44 a.m.
Created at: March 1, 2026, 8 p.m.