Triple

T645731
Position Surface form Disambiguated ID Type / Status
Subject U. S. Steel Košice E11237 entity
Predicate locatedIn P40 FINISHED
Object Košice Region E47856 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: Košice Region | Statement: [U. S. Steel Košice, locatedIn, Košice Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Košice Region
Context triple: [U. S. Steel Košice, locatedIn, Košice Region]
  • A. Trenčín
    Trenčín is a historic city in western Slovakia known for its medieval castle overlooking the Váh River and its role as a regional cultural and economic center.
  • B. Košice chosen
    Košice is a major city in eastern Slovakia known for its historic Old Town, Gothic St. Elisabeth Cathedral, and role as an important cultural and economic center.
  • C. Banská Bystrica
    Banská Bystrica is a historic central Slovak city best known as the main center of the anti-Nazi Slovak National Uprising during World War II.
  • D. Prešov
    Prešov is a historic city in eastern Slovakia known for its preserved medieval center and role as a regional cultural and economic hub.
  • E. Central Transdanubia
    Central Transdanubia is a region in western Hungary that includes historic cities such as Székesfehérvár and lies between the Danube River and Lake Balaton.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f1b24b08190897d8aedb877bd83 completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e331b148190aec0181dccbd5c62 completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:36 p.m.