Triple

T24385960
Position Surface form Disambiguated ID Type / Status
Subject Gmina Zator E614748 entity
Predicate bordersAdministrativeUnit P77012 FINISHED
Object Gmina Tomice
Gmina Tomice is a rural administrative district in southern Poland, located in Lesser Poland Voivodeship and known for its agricultural character and small villages.
E1631932 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: Gmina Tomice | Statement: [Gmina Zator, bordersAdministrativeUnit, Gmina Tomice]
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: Gmina Tomice
Triple: [Gmina Zator, bordersAdministrativeUnit, Gmina Tomice]
Generated description
Gmina Tomice is a rural administrative district in southern Poland, located in Lesser Poland Voivodeship and known for its agricultural character and small villages.

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_69e2d7e362e481909e32fe4ef8269d4f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29454c36c8190b7820dbf5af7b695 completed April 29, 2026, 11:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd67e6b148190b1e3ffb6194b32fd completed May 22, 2026, 4:07 a.m.
NEDg Description generation batch_6a0fd785e66c8190971031df082764bf completed May 22, 2026, 4:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd83e09ac81909c039cdcf5e2d022 completed May 22, 2026, 4:14 a.m.
Created at: April 18, 2026, 2:03 a.m.