Triple

T34634520
Position Surface form Disambiguated ID Type / Status
Subject Miyoshi E889382 entity
Predicate hasRiver P165 FINISHED
Object Basen River
The Basen River is a waterway flowing through the city of Miyoshi in Japan, contributing to the region’s local landscape and ecosystem.
E2133962 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: Basen River | Statement: [Miyoshi, hasRiver, Basen 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: Basen River
Triple: [Miyoshi, hasRiver, Basen River]
Generated description
The Basen River is a waterway flowing through the city of Miyoshi in Japan, contributing to the region’s local landscape and ecosystem.

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_69f349d724848190b63ad3407e0006d9 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7226aa5c081908fc693c6778462e7 completed May 3, 2026, 10:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a380f89c4f48190b97b1e927c35aaab completed June 21, 2026, 4:21 p.m.
NEDg Description generation batch_6a3810b5a55c8190809a5e755d9644c0 completed June 21, 2026, 4:26 p.m.
NED2 Entity disambiguation (via description) batch_6a38147a28c481909b3c22199083ba2c completed June 21, 2026, 4:42 p.m.
Created at: May 1, 2026, 2:04 a.m.