Triple

T14665998
Position Surface form Disambiguated ID Type / Status
Subject Hozu River E344373 entity
Predicate locatedNear P294 FINISHED
Object Sagano E143790 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: Sagano | Statement: [Hozu River, locatedNear, Sagano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sagano
Context triple: [Hozu River, locatedNear, Sagano]
  • A. Fujikawaguchiko
    Fujikawaguchiko is a Japanese resort town in Yamanashi Prefecture known for its views of Mount Fuji and Lake Kawaguchi, hot springs, and access to Fuji Five Lakes.
  • B. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • C. Sakuragaokacho
    Sakuragaokacho is a neighborhood in Tokyo’s Shibuya ward known for its urban atmosphere and proximity to Shibuya Station.
  • D. Osakasayama
    Osakasayama is a suburban city in Osaka Prefecture, Japan, known for its residential character and proximity to the Osaka metropolitan area.
  • E. Kameoka chosen
    Kameoka is a city in Kyoto Prefecture, Japan, known for its rural landscapes, historical sites, and proximity to Kyoto.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54c69f8819080a37161deecfba8 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cdc54a881909d9ea43c26b9d5ef completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:27 a.m.