Triple

T33460022
Position Surface form Disambiguated ID Type / Status
Subject Solikamsk E856885 entity
Predicate administrativeCenterOf P383 FINISHED
Object Solikamsky District
Solikamsky District is an administrative district (raion) in Perm Krai, Russia, centered around the city of Solikamsk and known for its industrial and resource-based economy.
E2288847 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: Solikamsky District | Statement: [Solikamsk, administrativeCenterOf, Solikamsky 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: Solikamsky District
Triple: [Solikamsk, administrativeCenterOf, Solikamsky District]
Generated description
Solikamsky District is an administrative district (raion) in Perm Krai, Russia, centered around the city of Solikamsk and known for its industrial and resource-based economy.

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_69f3497281a08190b4705de0b5f26ba7 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e4d2d66c819091d3c3a86ff2718e completed May 3, 2026, 6:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5ae31738588190aba2168cb762a961 completed July 18, 2026, 2:21 a.m.
NEDg Description generation batch_6a5ae37615088190822b3e234f3e5906 completed July 18, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_6a5ae3cd97ec81909d1b24601c441769 completed July 18, 2026, 2:24 a.m.
Created at: May 1, 2026, 1:37 a.m.