Triple

T12677647
Position Surface form Disambiguated ID Type / Status
Subject San River E302858 entity
Predicate flowsThrough P225 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: [San River, flowsThrough, Jarosław]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jarosław
Context triple: [San River, flowsThrough, 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b1dff48190923290555ece5d89 completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a341288190822fae2469efea09 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:20 p.m.