Triple

T2400550
Position Surface form Disambiguated ID Type / Status
Subject Warsaw Metro E47755 entity
Predicate connectsDistrict P2564 FINISHED
Object Wola E39215 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: Wola | Statement: [Warsaw Metro, connectsDistrict, Wola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wola
Context triple: [Warsaw Metro, connectsDistrict, Wola]
  • A. Mokotów
    Mokotów is a large, centrally located district of Warsaw known for its residential neighborhoods, parks, and business centers.
  • B. Ujazdów
    Ujazdów is a historic neighborhood in central Warsaw, known for its palaces, government buildings, and extensive green areas including parks and gardens.
  • C. Wola district chosen
    Wola district is a central borough of Warsaw, Poland, known for its historical significance, rapid postwar development, and mix of industrial heritage with modern urban infrastructure.
  • D. Wadowice
    Wadowice is a historic town in southern Poland best known as the birthplace of Pope John Paul II.
  • E. Bemowo
    Bemowo is a residential district in western Warsaw, Poland, known for its postwar housing estates, green areas, and growing transport links to the city 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc8c95d8c819088e4bb4fb32452ae completed March 7, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b6e2cb8819086a9714bd4720ed0 completed March 9, 2026, 8:19 p.m.
Created at: March 4, 2026, 7:57 p.m.