Triple

T15212671
Position Surface form Disambiguated ID Type / Status
Subject Prince of Volhynia E363554 entity
Predicate capital P234 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: [Prince of Volhynia, capital, Lutsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lutsk
Context triple: [Prince of Volhynia, capital, 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076c9e2481909d7a464b2172f4bf completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce894548190a19bab33285ad165 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:11 a.m.