Triple

T12129204
Position Surface form Disambiguated ID Type / Status
Subject Utrecht E288888 entity
Predicate hasRailwayStation P918 FINISHED
Object Utrecht Centraal E53552 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: Utrecht Centraal | Statement: [Utrecht, hasRailwayStation, Utrecht Centraal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utrecht Centraal
Context triple: [Utrecht, hasRailwayStation, Utrecht Centraal]
  • A. Utrecht Centraal chosen
    Utrecht Centraal is the largest and busiest railway station in the Netherlands, serving as a major national and international transport hub.
  • B. Leiden Centraal
    Leiden Centraal is the main railway station and transportation hub serving the Dutch city of Leiden in the Netherlands.
  • C. Amsterdam Centraal
    Amsterdam Centraal is the main railway hub of Amsterdam and one of the busiest train stations in the Netherlands, serving as a central gateway for national and international rail travel.
  • D. Rotterdam Centraal station
    Rotterdam Centraal station is a major railway terminal in the Dutch city of Rotterdam, serving as a key national and international transport hub.
  • E. Utrecht Central Station
    Utrecht Central Station is the main railway hub of the city of Utrecht in the Netherlands and one of the busiest train stations in the country.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158a2c2c8190aaff9d0cce177565 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef515488190957a69e1cc901d65 completed May 3, 2026, 7:53 a.m.
Created at: April 8, 2026, 9:49 p.m.