Triple

T15283140
Position Surface form Disambiguated ID Type / Status
Subject Jihlava E365320 entity
Predicate nearbyMajorCity P1982 FINISHED
Object Prague E14162 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: Prague | Statement: [Jihlava, nearbyMajorCity, Prague]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prague
Context triple: [Jihlava, nearbyMajorCity, Prague]
  • A. Prague chosen
    Prague is the historic capital city of the Czech Republic, renowned for its well-preserved medieval architecture, iconic Charles Bridge and Prague Castle, and vibrant cultural life.
  • B. Praga
    Praga is a historic district on the eastern bank of the Vistula River in Warsaw, Poland, known for its older architecture, cultural life, and role in the city's wartime history.
  • C. Kolín
    Kolín is a historic industrial town and important transport hub on the Elbe River in the Central Bohemian Region of the Czech Republic.
  • D. Brno
    Brno is the second-largest city in the Czech Republic, known as a major cultural, educational, and industrial center in the historical region of Moravia.
  • E. Prague-Libeň
    Prague-Libeň is a district of Prague, Czech Republic, historically notable as the site of the World War II Operation Anthropoid assassination of Reinhard Heydrich.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00e51f82081909f63d14b589d5587 completed April 15, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a6582908190a9a56652e9ccc5a1 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:15 a.m.