Triple

T13875247
Position Surface form Disambiguated ID Type / Status
Subject Gliwice E333563 entity
Predicate hasDistrict P459 FINISHED
Object Łabędy E95333 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: Łabędy | Statement: [Gliwice, hasDistrict, Łabędy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Łabędy
Context triple: [Gliwice, hasDistrict, Łabędy]
  • A. Łabuńka
    Łabuńka is a river in southeastern Poland that flows through the Lublin Voivodeship, including the area around the city of Zamość.
  • B. Bumar-Łabędy chosen
    Bumar-Łabędy is a Polish defense manufacturer best known for producing armored vehicles and modernized main battle tanks.
  • C. Łeba
    Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • D. Dzierzążnia
    Dzierzążnia is a village in east-central Poland that serves as a local rural settlement within Płońsk County in the Masovian Voivodeship.
  • E. Gubałówka
    Gubałówka is a popular hill and tourist destination in the Polish Tatra region, known for its panoramic views of Zakopane and the surrounding mountains.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be556708190bbcf0b3583f677e3 completed April 14, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c109ac5c819090b2b7e43334f904 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:15 p.m.