Triple

T38351671
Position Surface form Disambiguated ID Type / Status
Subject Łęknica E1046200 entity
Predicate nearbyTown P3883 FINISHED
Object Trzebiel
Trzebiel is a village in western Poland near the German border, known as the seat of its rural administrative district in the Lubusz Voivodeship.
E2295908 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: Trzebiel | Statement: [Łęknica, nearbyTown, Trzebiel]
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: Trzebiel
Triple: [Łęknica, nearbyTown, Trzebiel]
Generated description
Trzebiel is a village in western Poland near the German border, known as the seat of its rural administrative district in the Lubusz Voivodeship.

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_69f76e3a94fc81908edc175e8d259e80 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fcc6f7031081908ea134805c644d79 completed May 7, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a820bdc9238819089be4d53a64773b5 completed Aug. 16, 2026, 7:13 p.m.
NEDg Description generation batch_6a820c42e128819084c3cc3d4080245c completed Aug. 16, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_6a820c8446888190a588cf15e8ffc718 completed Aug. 16, 2026, 7:16 p.m.
Created at: May 3, 2026, 4:31 p.m.