Triple

T7263150
Position Surface form Disambiguated ID Type / Status
Subject Warsaw metropolitan area E159704 entity
Predicate containsCity P294 FINISHED
Object Nowy Dwór Mazowiecki E405547 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: Nowy Dwór Mazowiecki | Statement: [Warsaw metropolitan area, containsCity, Nowy Dwór Mazowiecki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nowy Dwór Mazowiecki
Context triple: [Warsaw metropolitan area, containsCity, Nowy Dwór Mazowiecki]
  • A. Nowy Dwór Mazowiecki chosen
    Nowy Dwór Mazowiecki is a town in east-central Poland, situated near Warsaw at the confluence of the Vistula and Narew rivers and known for hosting the Warsaw Modlin Airport.
  • B. Tomaszów Mazowiecki
    Tomaszów Mazowiecki is a town in central Poland known for its industrial heritage and proximity to natural attractions, including the Pilica River and the Sulejów Landscape Park.
  • C. Nowy Wiśnicz
    Nowy Wiśnicz is a historic town in southern Poland’s Lesser Poland Voivodeship, known for its well-preserved Renaissance castle and old town.
  • D. Mielec
    Mielec is a town in southeastern Poland known for its aviation industry and manufacturing sector.
  • E. Ostrołęka
    Ostrołęka is a town in east-central Poland known for its historical role in the Napoleonic Wars and as a local industrial and administrative 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac9fab88190881ab9e1cd94cdc1 completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69dbd9073c948190aa2e9e6b7ffe9022 completed April 12, 2026, 5:40 p.m.
Created at: March 27, 2026, 2:57 p.m.