Triple

T26051176
Position Surface form Disambiguated ID Type / Status
Subject Sofia City Province E647980 entity
Predicate includesAdministrativeUnit P3892 FINISHED
Object Vitosha district
Vitosha district is a municipal district in the southwestern part of Sofia, Bulgaria, named after the nearby Vitosha Mountain and encompassing a mix of urban neighborhoods and natural areas.
E1710491 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: Vitosha district | Statement: [Sofia City Province, includesAdministrativeUnit, Vitosha district]
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: Vitosha district
Triple: [Sofia City Province, includesAdministrativeUnit, Vitosha district]
Generated description
Vitosha district is a municipal district in the southwestern part of Sofia, Bulgaria, named after the nearby Vitosha Mountain and encompassing a mix of urban neighborhoods and natural 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_69e77e8d419481908004e6318d28aaab completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6065e26748190bac3160a91599913 completed May 2, 2026, 2:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a112741459881909a9b4e62a8a475d5 completed May 23, 2026, 4:04 a.m.
NEDg Description generation batch_6a1133f275508190ae6fe6b9c4596c6d completed May 23, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_6a113489dcec8190863da5dad0d717d9 completed May 23, 2026, 5 a.m.
Created at: April 22, 2026, 9:11 a.m.