Triple

T1532199
Position Surface form Disambiguated ID Type / Status
Subject Museumplein E32467 entity
Predicate bordersStreet P8235 FINISHED
Object Hobbemastraat E226996 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: Hobbemastraat | Statement: [Museumplein, bordersStreet, Hobbemastraat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hobbemastraat
Context triple: [Museumplein, bordersStreet, Hobbemastraat]
  • A. Vijzelstraat
    Vijzelstraat is a major street in central Amsterdam, Netherlands, running between the city’s historic canals and serving as an important traffic and commercial route.
  • B. Van Baerlestraat chosen
    Van Baerlestraat is a major street in Amsterdam known for running alongside the Museumplein and providing access to several prominent museums and cultural institutions.
  • C. Paleisstraat
    Paleisstraat is a central street in Amsterdam that runs alongside the Royal Palace and links Dam Square with the Jordaan area.
  • D. Kalverstraat
    Kalverstraat is one of Amsterdam’s busiest and most famous shopping streets, known for its dense concentration of retail stores and central location.
  • E. Utrechtsestraat
    Utrechtsestraat is a well-known shopping and dining street in central Amsterdam, noted for its historic canalside setting and mix of boutiques, cafés, and restaurants.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61dc6ab881908b22aa7a5295bf21 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fb455888190a1408a25b93a70ce completed March 9, 2026, 1:17 a.m.
Created at: March 4, 2026, 7:26 p.m.