Triple

T33974183
Position Surface form Disambiguated ID Type / Status
Subject Isahaya E871082 entity
Predicate hasRiver P165 FINISHED
Object Honmyo River
Honmyo River is a river flowing through Isahaya in Nagasaki Prefecture, Japan, contributing to the city's landscape and local water system.
E2292138 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: Honmyo River | Statement: [Isahaya, hasRiver, Honmyo 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: Honmyo River
Triple: [Isahaya, hasRiver, Honmyo River]
Generated description
Honmyo River is a river flowing through Isahaya in Nagasaki Prefecture, Japan, contributing to the city's landscape and local water 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_69f3499da0188190ab1a4ff06fb06a2a completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70328cbe88190b14ba4c378c3ac07 completed May 3, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5cc2abae3481909abdd7aa42290f9d completed July 19, 2026, 12:27 p.m.
NEDg Description generation batch_6a5cc5cbfa748190a12396026413df85 completed July 19, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_6a5cc6c3b9dc81908efd4437f608edbc completed July 19, 2026, 12:44 p.m.
Created at: May 1, 2026, 1:50 a.m.