Triple

T17295982
Position Surface form Disambiguated ID Type / Status
Subject Targówek E419910 entity
Predicate hasNeighbour P5707 FINISHED
Object Białołęka E905830 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: Białołęka | Statement: [Targówek, hasNeighbour, Białołęka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Białołęka
Context triple: [Targówek, hasNeighbour, Białołęka]
  • A. Białołęka chosen
    Białołęka is a rapidly developing residential district in the northeastern part of Warsaw, known for its modern housing estates and expanding infrastructure.
  • B. Biała Lądecka
    Biała Lądecka is a river in southwestern Poland that flows through the Kłodzko region before joining the Nysa Kłodzka.
  • C. Bukowiec
    Bukowiec is a village in southwestern Poland known for its scenic location in the Karkonosze foothills and historic park-and-palace complex.
  • D. Biała
    Biała is a former town in southern Poland that historically developed as a separate urban center before being merged with Bielsko to form the modern city of Bielsko-Biała.
  • E. Biała
    Biała is a river in southern Poland known for flowing through the city of Bielsko-Biała before joining the Vistula basin.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e437875b208190bcf0df2ded546257 completed April 19, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180d881ec81908e794143d355effe completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:40 a.m.