Triple

T802495
Position Surface form Disambiguated ID Type / Status
Subject Wrocław E17157 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: [Wrocław, twinCity, Lviv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lviv
Context triple: [Wrocław, 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. Banská Bystrica
    Banská Bystrica is a historic central Slovak city best known as the main center of the anti-Nazi Slovak National Uprising during World War II.
  • D. Košice
    Košice is a major city in eastern Slovakia known for its historic Old Town, Gothic St. Elisabeth Cathedral, and role as an important cultural and economic center.
  • E. Zhytomyr
    Zhytomyr is a historic city in northwestern Ukraine known as an important regional center and the birthplace of pioneering rocket engineer Sergei Korolev.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabd9fc081908ccadd8e8769de2d completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c7103a00819087ad711a2ab99770 completed March 4, 2026, 5:45 a.m.
Created at: March 1, 2026, 7:38 p.m.