Triple

T31857166
Position Surface form Disambiguated ID Type / Status
Subject Mrass dialect E813228 entity
Predicate spokenAlong P24200 FINISHED
Object Mrass River
The Mrass River is a waterway in southwestern Siberia, Russia, along whose banks the indigenous Shor people traditionally live and speak the Mrass dialect.
E2288038 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: Mrass River | Statement: [Mrass dialect, spokenAlong, Mrass River]
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: Mrass River
Triple: [Mrass dialect, spokenAlong, Mrass River]
Generated description
The Mrass River is a waterway in southwestern Siberia, Russia, along whose banks the indigenous Shor people traditionally live and speak the Mrass dialect.

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_69f348ebf32881908d9439646933dc76 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6b06a8fdc819090bbb2d491bb2a35 completed May 3, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5a5d8b1b2c8190be4d03af0cf54b51 completed July 17, 2026, 4:51 p.m.
NEDg Description generation batch_6a5a5ede143c8190b950f1b56bbd9df0 completed July 17, 2026, 4:57 p.m.
NED2 Entity disambiguation (via description) batch_6a5a5f44a25c81909beb4bc401446304 completed July 17, 2026, 4:58 p.m.
Created at: April 30, 2026, 11:52 p.m.