Triple

T27295441
Position Surface form Disambiguated ID Type / Status
Subject Alapayevsk E688749 entity
Predicate locatedOn P40 FINISHED
Object Neyva River
The Neyva River is a waterway in Russia’s Sverdlovsk Oblast that flows through several industrial towns, including Alapayevsk, before contributing to the Ob river basin.
 E2293352 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: Neyva River | Statement: [Alapayevsk, locatedOn, Neyva 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: Neyva River
Triple: [Alapayevsk, locatedOn, Neyva River]
Generated description
The Neyva River is a waterway in Russia’s Sverdlovsk Oblast that flows through several industrial towns, including Alapayevsk, before contributing to the Ob river basin.

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_69ef355a96308190a2bed991525fb278 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6277f37208190a33476a7a3bddec6 completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a94ab30f881908590de5bddd3bf8d completed Aug. 11, 2026, 3:19 a.m.
NEDg Description generation batch_6a7a95184cdc8190b67c5551f37db0b0 completed Aug. 11, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_6a7a956df9e88190a1a7007169464986 completed Aug. 11, 2026, 3:22 a.m.
Created at: April 27, 2026, 11:18 a.m.