Triple

T75520
Position Surface form Disambiguated ID Type / Status
Subject Poles E1509 entity
Predicate populationCenter P2106 FINISHED
Object Warsaw E8399 NE FINISHED

How this triple was built (3 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: Warsaw | Statement: [Poles, populationCenter, Warsaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warsaw
Context triple: [Poles, populationCenter, Warsaw]
  • A. Warsaw chosen
    Warsaw is the capital and largest city of Poland, known for its resilient history, especially its near-total destruction in World War II and subsequent postwar reconstruction.
  • B. Kraków
    Kraków is one of Poland’s oldest and most historically significant cities, renowned for its well-preserved medieval core, royal heritage, and cultural institutions.
  • C. Wilno
    Wilno is the historical Polish name for Vilnius, a major cultural and political center of the region that served as an important city in the interwar Second Polish Republic.
  • D. Łódź
    Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
  • E. Poznań
    Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: populationCenter
Context triple: [Poles, populationCenter, Warsaw]
  • A. hasPopulationCenter chosen
    Indicates that an area, region, or administrative unit contains or is served by a primary settlement or population hub.
  • B. cityPopulationContext
    Indicates the contextual relationship between a city and information about its population, such as size, distribution, or demographic characteristics.
  • C. populationDensity
    Indicates the number of individuals or entities occupying a unit area within a given region.
  • D. isMajorCenterOf
    Indicates that a place serves as a primary hub or focal point for a particular activity, function, or domain.
  • E. metropolitanAreaPopulationApproximate
    Indicates that the predicate specifies an approximate total population size for a given metropolitan area.
  • F. None of above.

Provenance (4 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a25314bd6c81908d1cfd4b83f20049 completed Feb. 28, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2b014ab2c8190bcef8382280932dc completed Feb. 28, 2026, 9:06 a.m.
PD Predicate disambiguation batch_69a24eae77ec81909015906f31f2b62e completed Feb. 28, 2026, 2:10 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.