Triple

T11916828
Position Surface form Disambiguated ID Type / Status
Subject Hertz E283545 entity
Predicate locatedIn P40 FINISHED
Object city of Utrecht E288888 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: city of Utrecht | Statement: [Hertz, locatedIn, city of Utrecht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Utrecht
Context triple: [Hertz, locatedIn, city of Utrecht]
  • A. Utrecht
    Utrecht is a historic city and province in the central Netherlands, known for its medieval old town, canals, and role as a religious and cultural center.
  • B. New Utrecht
    New Utrecht is a historic neighborhood in the southwestern part of Brooklyn, New York City, originally founded as a Dutch town in the 17th century.
  • C. Utrecht, Netherlands chosen
    Utrecht is a historic Dutch city known for its medieval old town, prominent religious and educational institutions, and role as a major cultural and economic center in the Netherlands.
  • D. Haarlem
    Haarlem is a historic Dutch city in the province of North Holland, known for its medieval architecture, cultural heritage, and role as a regional center near Amsterdam.
  • E. Rotterdam
    Rotterdam is a major Dutch port city known for having one of the world’s largest harbors and striking modern architecture.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8deb14881909b65a1f159aec65f completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e37032c819087c46c7adda94cd9 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:44 p.m.