Triple

T10131979
Position Surface form Disambiguated ID Type / Status
Subject Rivne E226359 entity
Predicate hasRailwayConnectionTo P3791 FINISHED
Object Lutsk E6073 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: Lutsk | Statement: [Rivne, hasRailwayConnectionTo, Lutsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lutsk
Context triple: [Rivne, hasRailwayConnectionTo, Lutsk]
  • A. Lutsk chosen
    Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
  • B. Drohobych
    Drohobych is a historic city in western Ukraine known for its medieval architecture, salt production heritage, and association with writer and artist Bruno Schulz.
  • C. Ternopil
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • D. Rivne
    Rivne is a city in western Ukraine that serves as an important regional administrative, economic, and cultural center.
  • E. Cherkasy
    Cherkasy is a city in central Ukraine located on the banks of the Dnieper River and serving as an important regional industrial 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd33557a88190b5fb1938646d8532 completed April 2, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d95e38789881909e45e8d0b0489a59 completed April 10, 2026, 8:31 p.m.
Created at: March 30, 2026, 9:06 p.m.