Triple

T30045474
Position Surface form Disambiguated ID Type / Status
Subject Batalpashinskaya E763439 entity
Predicate administrativeCenterOf P383 FINISHED
Object Batalpashinsky Okrug
Batalpashinsky Okrug was an administrative district of the Russian Empire and early Soviet Russia in the North Caucasus region, centered around the town of Batalpashinskaya.
E1921717 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: Batalpashinsky Okrug | Statement: [Batalpashinskaya, administrativeCenterOf, Batalpashinsky Okrug]
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: Batalpashinsky Okrug
Triple: [Batalpashinskaya, administrativeCenterOf, Batalpashinsky Okrug]
Generated description
Batalpashinsky Okrug was an administrative district of the Russian Empire and early Soviet Russia in the North Caucasus region, centered around the town of Batalpashinskaya.

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_69f22470a89c8190be7273297c0e0d19 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67a11bf2c81908a5e9fb6c3ef7752 completed May 2, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2856d87cd48190bfe18c3ab96152f6 completed June 9, 2026, 6:09 p.m.
NEDg Description generation batch_6a2857f33c9481908e96e48c853ce11b completed June 9, 2026, 6:14 p.m.
NED2 Entity disambiguation (via description) batch_6a28585f785c8190b018169074dc4425 completed June 9, 2026, 6:15 p.m.
Created at: April 29, 2026, 6:54 p.m.