Triple

T31297019
Position Surface form Disambiguated ID Type / Status
Subject Gmina Michałowo E798106 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Michałowo
Michałowo is a small town in northeastern Poland, near the border with Belarus, known for its proximity to the Białowieża Forest and its multicultural heritage.
E1958649 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: Michałowo | Statement: [Gmina Michałowo, hasAdministrativeCenter, Michałowo]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Michałowo
Triple: [Gmina Michałowo, hasAdministrativeCenter, Michałowo]
Generated description
Michałowo is a small town in northeastern Poland, near the border with Belarus, known for its proximity to the Białowieża Forest and its multicultural heritage.

Provenance (5 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_69f224dfde288190af313f3c221c857e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69e31c0ac8190a39cff8445b2ede0 completed May 3, 2026, 1 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a7204de348190bd76c13a2558adfb completed June 11, 2026, 8:29 a.m.
NEDg Description generation batch_6a2a72bf3c0c8190825cbabd2097dea6 completed June 11, 2026, 8:33 a.m.
NED2 Entity disambiguation (via description) batch_6a2a95427bf8819087f212d19481feeb completed June 11, 2026, 11 a.m.
Created at: April 29, 2026, 9:14 p.m.