Triple

T7793003
Position Surface form Disambiguated ID Type / Status
Subject Pärnu E180225 entity
Predicate hasTwinTown P919 FINISHED
Object Šiauliai E556607 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: Šiauliai | Statement: [Pärnu, hasTwinTown, Šiauliai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Šiauliai
Context triple: [Pärnu, hasTwinTown, Šiauliai]
  • A. Šiauliai chosen
    Šiauliai is one of the largest cities in Lithuania, known as a regional industrial and cultural center in the northern part of the country.
  • B. Šilutė
    Šilutė is a town in western Lithuania known for its location near the Nemunas River delta and its historical ties to the former East Prussian region.
  • C. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • D. Telšiai
    Telšiai is a historic city in northwestern Lithuania that serves as the cultural and administrative center of the Samogitia region.
  • E. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae938714c8190b89917e6ded004da completed March 30, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb13dbe1f88190bde2c5c76dcfeb8f completed March 31, 2026, 12:22 a.m.
Created at: March 30, 2026, 4:31 p.m.