Triple

T25610029
Position Surface form Disambiguated ID Type / Status
Subject Kharp E642021 entity
Predicate locatedInAdministrativeTerritorialEntity P40 FINISHED
Object Priuralsky District
Priuralsky District is an administrative district in the Yamalo-Nenets Autonomous Okrug of Russia, known for its Arctic location and sparsely populated tundra landscapes.
E2015669 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: Priuralsky District | Statement: [Kharp, locatedInAdministrativeTerritorialEntity, Priuralsky 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: Priuralsky District
Triple: [Kharp, locatedInAdministrativeTerritorialEntity, Priuralsky District]
Generated description
Priuralsky District is an administrative district in the Yamalo-Nenets Autonomous Okrug of Russia, known for its Arctic location and sparsely populated tundra landscapes.

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_6a3485e26c948190a519564467e44fe1 completed June 18, 2026, 11:57 p.m.
NEDg Description generation batch_6a3488ed6db88190af9197eb63f35313 completed June 19, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a348a6e63bc8190a6df0a77a51245cc completed June 19, 2026, 12:16 a.m.
Created at: April 21, 2026, 4:40 p.m.