Triple

T24778235
Position Surface form Disambiguated ID Type / Status
Subject Siberian economic region E619919 entity
Predicate borderedBy P224 FINISHED
Object Ural economic region
The Ural economic region is a major industrial and mining area of Russia centered around the Ural Mountains, serving as a key bridge between European and Siberian parts of the country.
E51691 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: Ural economic region | Statement: [Siberian economic region, borderedBy, Ural economic region]
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: Ural economic region
Triple: [Siberian economic region, borderedBy, Ural economic region]
Generated description
The Ural economic region is a major industrial and mining area of Russia centered around the Ural Mountains, serving as a key bridge between European and Siberian parts of the country.

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_69e2fabdbe8c8190adbb9434b8636cad completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410d4c130819095f227ff5b500bdc completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c1f6e348190bc924bb8c65c46af completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a10273b405c8190b9a68a74c92b9e7b completed May 22, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_6a1027f5bdd4819081cf55a1ad77b4ab completed May 22, 2026, 9:55 a.m.
Created at: April 18, 2026, 4:41 a.m.