Triple

T26479301
Position Surface form Disambiguated ID Type / Status
Subject Vratsa Province E664628 entity
Predicate hasMunicipality P847 FINISHED
Object Hayredin Municipality
Hayredin Municipality is a local administrative region in northwestern Bulgaria, centered around the village of Hayredin and governed as part of Vratsa Province.
E1728719 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: Hayredin Municipality | Statement: [Vratsa Province, hasMunicipality, Hayredin Municipality]
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: Hayredin Municipality
Triple: [Vratsa Province, hasMunicipality, Hayredin Municipality]
Generated description
Hayredin Municipality is a local administrative region in northwestern Bulgaria, centered around the village of Hayredin and governed as part of Vratsa Province.

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_69ee883bc85481909885f92415cbce33 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612cf14a88190a72376131be70e05 completed May 2, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11bb2188f8819095253d2dbb188779 completed May 23, 2026, 2:35 p.m.
NEDg Description generation batch_6a11be5f621881908d83370dd283a10f completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf7e1de48190ba8ed044628d5bf7 completed May 23, 2026, 2:53 p.m.
Created at: April 27, 2026, 12:25 a.m.