Triple

T15899155
Position Surface form Disambiguated ID Type / Status
Subject Omo River E385538 entity
Predicate hasTributary P415 FINISHED
Object Usno River
The Usno River is a tributary watercourse in southwestern Ethiopia that feeds into the Omo River within the East African Rift Valley.
E1831438 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: Usno River | Statement: [Omo River, hasTributary, Usno 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: Usno River
Triple: [Omo River, hasTributary, Usno River]
Generated description
The Usno River is a tributary watercourse in southwestern Ethiopia that feeds into the Omo River within the East African Rift Valley.

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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563bd0688190b6f7a695be0a4625 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf054c1481908fb39844c895112a completed June 1, 2026, 12:15 a.m.
NEDg Description generation batch_6a1cd020780c81908d33cd9d1676a762 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a24947d54208190bbc915f3e5d8295a completed June 6, 2026, 9:43 p.m.
Created at: April 10, 2026, 4:51 a.m.