Triple

T12635634
Position Surface form Disambiguated ID Type / Status
Subject Borna station E301755 entity
Predicate locatedIn P40 FINISHED
Object Borna E185203 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: Borna | Statement: [Borna station, locatedIn, Borna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borna
Context triple: [Borna station, locatedIn, Borna]
  • A. Borna chosen
    Borna is a town in the German state of Saxony that serves as an administrative and economic center in the Leipzig region.
  • B. Temišvar
    Temišvar is the Serbian name for Timișoara, a major cultural and economic city in western Romania known for its historical architecture and role in the 1989 Romanian Revolution.
  • C. Borsad
    Borsad is a town in the Indian state of Gujarat known for its agricultural markets and role as a local commercial center.
  • D. Jérica
    Jérica is a historic municipality in the province of Castellón, in Spain’s Valencian Community, known for its medieval architecture and prominent Mudejar-style bell tower.
  • E. Dravograd
    Dravograd is a small Slovenian town in the Carinthia region, known for its location at the confluence of the Drava and Meža rivers and its historical role as a regional 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96147f49c8190b701e1e27e207a95 completed April 10, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f66873706c8190a9908d1a8629b1c5 completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:16 p.m.