Triple

T21362561
Position Surface form Disambiguated ID Type / Status
Subject Lubliniec E526820 entity
Predicate locatedInAdministrativeUnit P40 FINISHED
Object Lubliniec County
Lubliniec County is an administrative district (powiat) in the Silesian Voivodeship of southern Poland, encompassing the town of Lubliniec and surrounding areas.
E1686915 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: Lubliniec County | Statement: [Lubliniec, locatedInAdministrativeUnit, Lubliniec County]
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: Lubliniec County
Triple: [Lubliniec, locatedInAdministrativeUnit, Lubliniec County]
Generated description
Lubliniec County is an administrative district (powiat) in the Silesian Voivodeship of southern Poland, encompassing the town of Lubliniec and surrounding areas.

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_69e0b51d8a308190b09113b3b3f9bc15 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5bad6a308190a9665734a0fb5f55 completed April 26, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b6f49d588190960982c7aead9b7b completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b84949448190ba06c85d0f19215b completed May 22, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9651af481909206495b2fc57a2e completed May 22, 2026, 8:15 p.m.
Created at: April 16, 2026, 5:08 p.m.