Triple

T30256576
Position Surface form Disambiguated ID Type / Status
Subject Mzymta River E769363 entity
Predicate hasTributary P415 FINISHED
Object Achipse River
The Achipse River is a smaller watercourse in southwestern Russia that feeds into the Mzymta River in the Western Caucasus region.
E2294954 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: Achipse River | Statement: [Mzymta River, hasTributary, Achipse 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: Achipse River
Triple: [Mzymta River, hasTributary, Achipse River]
Generated description
The Achipse River is a smaller watercourse in southwestern Russia that feeds into the Mzymta River in the Western Caucasus region.

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_69f22484a5f48190b678cd607700bc82 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f680a511708190a208959af5a8d016 completed May 2, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c4919c8d881909eee5cd61e6055c1 completed Aug. 12, 2026, 10:21 a.m.
NEDg Description generation batch_6a7c49a7f42c819088cdac78be9a038d completed Aug. 12, 2026, 10:23 a.m.
NED2 Entity disambiguation (via description) batch_6a7c5625976081909c92967f801438a0 completed Aug. 12, 2026, 11:16 a.m.
Created at: April 29, 2026, 7:41 p.m.