Triple

T13267211
Position Surface form Disambiguated ID Type / Status
Subject Humenné E315952 entity
Predicate hasTwinTown P919 FINISHED
Object Jarosław E284545 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: Jarosław | Statement: [Humenné, hasTwinTown, Jarosław]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jarosław
Context triple: [Humenné, hasTwinTown, Jarosław]
  • A. Jarosław chosen
    Jarosław is a historic town in southeastern Poland known for its well-preserved Old Town and role as a former important trade center.
  • B. Jasło
    Jasło is a small town in southeastern Poland, known as part of the historical region of Galicia and for its cultural and educational traditions.
  • C. Hrubieszów
    Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
  • D. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • E. Ostrołęka
    Ostrołęka is a town in east-central Poland known for its historical role in the Napoleonic Wars and as a local industrial and administrative 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901e44bc8190966f87ae219d6bf4 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a4cc20881909b1ca6623e5b1988 completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:25 p.m.