Triple

T9685871
Position Surface form Disambiguated ID Type / Status
Subject Northern Great Plain E234405 entity
Predicate containsCity P294 FINISHED
Object Tiszaújváros E306629 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: Tiszaújváros | Statement: [Northern Great Plain, containsCity, Tiszaújváros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiszaújváros
Context triple: [Northern Great Plain, containsCity, Tiszaújváros]
  • A. Tiszaújváros chosen
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • B. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • C. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • D. Balmazújváros
    Balmazújváros is a town in eastern Hungary known for its agricultural surroundings and location near the Hortobágy National Park.
  • E. Gyulafehérvár
    Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
  • 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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9cd2dab481908e0d3fed28de9d40 completed April 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2ffd03dac81909f6c91afb8d49521 completed April 6, 2026, 12:35 a.m.
Created at: March 30, 2026, 8:16 p.m.