Triple

T12908471
Position Surface form Disambiguated ID Type / Status
Subject European Netherlands E308787 entity
Predicate containsMajorCity P316 FINISHED
Object Eindhoven E13694 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: Eindhoven | Statement: [European Netherlands, containsMajorCity, Eindhoven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eindhoven
Context triple: [European Netherlands, containsMajorCity, Eindhoven]
  • A. Eindhoven chosen
    Eindhoven is a major city in the southern Netherlands known for its industrial and technological significance, particularly as a hub for electronics and design.
  • B. Tilburg
    Tilburg is a city in the southern Netherlands known historically as an industrial and textile center and now as a regional cultural and educational hub.
  • C. Nijmegen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • D. Heerlen
    Heerlen is a city in the southeastern Netherlands known for its mining history and modernist architecture, located in the province of Limburg.
  • E. 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.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9719d4d1c8190a2c4f362e1772a73 completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c1d31048190ab0a8d8e00515211 completed May 8, 2026, 2:36 a.m.
Created at: April 9, 2026, 5:41 p.m.