Triple

T11895564
Position Surface form Disambiguated ID Type / Status
Subject Dunajská Streda E283026 entity
Predicate hasTwinTown P919 FINISHED
Object Komárom (Hungary) E954175 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: Komárom (Hungary) | Statement: [Dunajská Streda, hasTwinTown, Komárom (Hungary)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komárom (Hungary)
Context triple: [Dunajská Streda, hasTwinTown, Komárom (Hungary)]
  • A. Komárom chosen
    Komárom is a Hungarian town on the Danube River known for its historic fortifications and its twin-city relationship with Komárno in Slovakia.
  • B. Komló
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • C. Kaposvár, Hungary
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • D. Kisvárda, Hungary
    Kisvárda is a small town in northeastern Hungary known for its historic castle, thermal baths, and role as a regional cultural and economic center.
  • E. Komárno
    Komárno is a historic town and river port in southern Slovakia, situated at the confluence of the Danube and Váh rivers on the border with Hungary.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1286808190949719f54ff49a01 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f49ce47d488190af7f832e7719a4ce completed May 1, 2026, 12:30 p.m.
Created at: April 8, 2026, 9:44 p.m.