Triple

T12041953
Position Surface form Disambiguated ID Type / Status
Subject Stříbro E286682 entity
Predicate hasRegionCapital P16248 FINISHED
Object Plzeň E19529 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: Plzeň | Statement: [Stříbro, hasRegionCapital, Plzeň]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plzeň
Context triple: [Stříbro, hasRegionCapital, Plzeň]
  • A. Plzeň chosen
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • B. Pardubice
    Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
  • C. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • D. Žatec
    Žatec is a historic Czech town in the Ústí nad Labem Region renowned for its long-standing hop-growing tradition and beer production.
  • E. Jihlava
    Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040d13108190bd1a969fa62aae5a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a114ccc81909bc428c40c01a461 completed May 3, 2026, 8:40 a.m.
Created at: April 8, 2026, 9:47 p.m.