Triple

T16715209
Position Surface form Disambiguated ID Type / Status
Subject Nemunas River E406206 entity
Predicate flowsThrough P225 FINISHED
Object Druskininkai E613767 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: Druskininkai | Statement: [Nemunas River, flowsThrough, Druskininkai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Druskininkai
Context triple: [Nemunas River, flowsThrough, Druskininkai]
  • A. Druskininkai chosen
    Druskininkai is a well-known spa and resort town in southern Lithuania, famous for its mineral springs and wellness tourism.
  • B. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • C. Rokiškis
    Rokiškis is a town in northeastern Lithuania known for its well-preserved manor, historic architecture, and role as a regional cultural center.
  • D. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • E. Sakiai
    Sakiai is a small town in southwestern Lithuania known for its proximity to the Russian and Polish borders and its role as a local administrative and cultural 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38654ee4c8190abf36c29d6610a96 completed April 18, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d3adef081908692a4a86d7a0779 completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.