Triple

T10309583
Position Surface form Disambiguated ID Type / Status
Subject Hajdú-Bihar County E241851 entity
Predicate containsCity P294 FINISHED
Object Püspökladány E815345 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: Püspökladány | Statement: [Hajdú-Bihar County, containsCity, Püspökladány]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Püspökladány
Context triple: [Hajdú-Bihar County, containsCity, Püspökladány]
  • A. Püspökladány chosen
    Püspökladány is a town in eastern Hungary known for its location on the Great Hungarian Plain and its role as a local agricultural and transport hub.
  • B. Pusztaszabolcs
    Pusztaszabolcs is a small town in central Hungary known for its role as a local railway junction and residential community within Fejér County.
  • C. Párkány
    Párkány is a town on the Danube River in southern Slovakia, near the Hungarian border, historically known as a strategic site of conflicts between the Habsburg and Ottoman empires.
  • D. Törökszentmiklós
    Törökszentmiklós is a town in central-eastern Hungary known for its agricultural surroundings and location within the Great Hungarian Plain.
  • E. Bicske
    Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32a18ac81909b4efd8c1ba3e113 completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d7154b88190a0ae1dfa029b125e completed April 9, 2026, 3:30 a.m.
Created at: April 6, 2026, 11:47 a.m.