Triple

T2153264
Position Surface form Disambiguated ID Type / Status
Subject Lublin E47827 entity
Predicate twinCity P1072 FINISHED
Object Lviv E13495 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: Lviv | Statement: [Lublin, twinCity, Lviv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lviv
Context triple: [Lublin, twinCity, Lviv]
  • A. Lutsk
    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. Lwów chosen
    Lwów is a historic city in Eastern Europe, now known as Lviv in western Ukraine, long recognized as a major cultural and political center of the region.
  • C. Rzeszów
    Rzeszów is a major city in southeastern Poland known as an important economic, academic, and cultural center of the region.
  • D. Uzhhorod
    Uzhhorod is a historic city in western Ukraine near the Slovak and Hungarian borders, known for its multicultural heritage and as the administrative center of Zakarpattia Oblast.
  • E. 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.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe4a3b608190b3bd5d8e28534090 completed March 7, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69b20f1577388190bc95b2151af55732 completed March 12, 2026, 12:55 a.m.
Created at: March 4, 2026, 7:44 p.m.