Triple

T35306126
Position Surface form Disambiguated ID Type / Status
Subject Vyatskiye Polyany E1019640 entity
Predicate administrativeCenterOf P383 FINISHED
Object Vyatskopolyansky District
Vyatskopolyansky District is an administrative district (raion) in Kirov Oblast, Russia, located in the southeastern part of the region.
E2290493 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: Vyatskopolyansky District | Statement: [Vyatskiye Polyany, administrativeCenterOf, Vyatskopolyansky 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: Vyatskopolyansky District
Triple: [Vyatskiye Polyany, administrativeCenterOf, Vyatskopolyansky District]
Generated description
Vyatskopolyansky District is an administrative district (raion) in Kirov Oblast, Russia, located in the southeastern part of the region.

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_69f76de8b4c48190ae504b86185c474c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7904fd0248190899e6266e3a6b023 completed May 3, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5bd44801108190ba1bba01056ee49d completed July 18, 2026, 7:30 p.m.
NEDg Description generation batch_6a5bd4b150508190bce1373311b8bf3b completed July 18, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_6a5bd66b66788190a9cea71737a48b99 completed July 18, 2026, 7:39 p.m.
Created at: May 3, 2026, 4:03 p.m.