Triple

T5688741
Position Surface form Disambiguated ID Type / Status
Subject Powązki Military Cemetery E125376 entity
Predicate locatedInNeighborhood P40 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: [Powązki Military Cemetery, locatedInNeighborhood, Wola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wola
Context triple: [Powązki Military Cemetery, locatedInNeighborhood, Wola]
  • A. Mokotów
    Mokotów is a large, centrally located district of Warsaw known for its residential neighborhoods, parks, and business centers.
  • B. Bielany
    Bielany is a northern district of Warsaw, Poland, known for its residential neighborhoods, green spaces, and connection to the city center via the Warsaw Metro.
  • C. Ujazdów
    Ujazdów is a historic neighborhood in central Warsaw, known for its palaces, government buildings, and extensive green areas including parks and gardens.
  • D. Zduńska Wola
    Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
  • E. 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.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e1c6148190aeae7620bd9ee9d4 completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c124e449d481909a6aa8e1c6494322 completed March 23, 2026, 11:32 a.m.
Created at: March 22, 2026, 3:44 p.m.