Triple

T25609910
Position Surface form Disambiguated ID Type / Status
Subject Pokrov E642018 entity
Predicate locatedOnTerritoryOf P17086 FINISHED
Object Petushinsky District
Petushinsky District is an administrative and municipal district in Vladimir Oblast, Russia, known for encompassing the town of Pokrov and lying along major transportation routes between Moscow and the Volga region.
E1707707 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: Petushinsky District | Statement: [Pokrov, locatedOnTerritoryOf, Petushinsky 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: Petushinsky District
Triple: [Pokrov, locatedOnTerritoryOf, Petushinsky District]
Generated description
Petushinsky District is an administrative and municipal district in Vladimir Oblast, Russia, known for encompassing the town of Pokrov and lying along major transportation routes between Moscow and the Volga 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_69e75dc6ccf081908d49578fd36a76d5 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9e1f1408190bab690f67f7d3a31 completed May 2, 2026, 1:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111ae9a4b48190b3e0c7baf956a9d1 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111d1eb3788190990ca419c1aea4c0 completed May 23, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_6a111d5243e48190900c6296f6c40b9c completed May 23, 2026, 3:21 a.m.
Created at: April 21, 2026, 4:40 p.m.