Triple

T21387036
Position Surface form Disambiguated ID Type / Status
Subject Yug River E527529 entity
Predicate hasTributary P415 FINISHED
Object Sharzhenga River
The Sharzhenga River is a watercourse in Russia that serves as one of the tributaries feeding into the larger Yug River system.
E2091633 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: Sharzhenga River | Statement: [Yug River, hasTributary, Sharzhenga 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: Sharzhenga River
Triple: [Yug River, hasTributary, Sharzhenga River]
Generated description
The Sharzhenga River is a watercourse in Russia that serves as one of the tributaries feeding into the larger Yug River system.

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_69e0b51ff3748190935c0a513c62a12b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee62cb05288190a894f33850e22c03 completed April 26, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a36f9a286e48190a10d8f6b39756274 completed June 20, 2026, 8:35 p.m.
NEDg Description generation batch_6a36fb468d248190ada52608298a4ef2 completed June 20, 2026, 8:42 p.m.
NED2 Entity disambiguation (via description) batch_6a36fbdbfd7881909e5088bedded00a3 completed June 20, 2026, 8:45 p.m.
Created at: April 16, 2026, 5:12 p.m.