Triple

T26474695
Position Surface form Disambiguated ID Type / Status
Subject Mitaka, Tokyo, Japan E665994 entity
Predicate hasRiver P165 FINISHED
Object Nogawa River
Nogawa River is a small urban river in western Tokyo, Japan, known for the parks and green spaces that line its banks.
 E580436 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: Nogawa River | Statement: [Mitaka, Tokyo, Japan, hasRiver, Nogawa 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: Nogawa River
Triple: [Mitaka, Tokyo, Japan, hasRiver, Nogawa River]
Generated description
Nogawa River is a small urban river in western Tokyo, Japan, known for the parks and green spaces that line its banks.

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_69ee883f80dc819090e311b022b78e02 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612cbbd188190bf01aede80ba1db5 completed May 2, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d6582b148190bc4595659faf4828 completed June 28, 2026, 8:07 a.m.
NEDg Description generation batch_6a40d88e2bf48190ba6b3040ea8559b8 completed June 28, 2026, 8:17 a.m.
NED2 Entity disambiguation (via description) batch_6a40d8f9142081908a71318aad0e4c8b completed June 28, 2026, 8:19 a.m.
Created at: April 27, 2026, 12:22 a.m.