Triple

T25311618
Position Surface form Disambiguated ID Type / Status
Subject Polish Episcopal Conference E634619 entity
Predicate abbreviation P43 FINISHED
Object KEP
KEP is the commonly used abbreviation for the Polish Episcopal Conference, the central assembly of Catholic bishops in Poland.
E1676280 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: KEP | Statement: [Polish Episcopal Conference, abbreviation, KEP]
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: KEP
Triple: [Polish Episcopal Conference, abbreviation, KEP]
Generated description
KEP is the commonly used abbreviation for the Polish Episcopal Conference, the central assembly of Catholic bishops in Poland.

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_69e75a9847c08190bb02990d06d5ffb7 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4939f4e58819095eba5792f55f07c completed May 1, 2026, 11:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1075e1030c8190a6dfc36164d8c0d8 completed May 22, 2026, 3:27 p.m.
NEDg Description generation batch_6a10771a5a648190844a509e6ac507be completed May 22, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_6a1077bbf9448190bee4351dcb985c0c completed May 22, 2026, 3:35 p.m.
Created at: April 21, 2026, 1:27 p.m.