Triple

T23938814
Position Surface form Disambiguated ID Type / Status
Subject Nachi-no-Hi Matsuri E602721 entity
Predicate location P40 FINISHED
Object Nachi Katsuura
Nachi Katsuura is a coastal town in Wakayama Prefecture, Japan, renowned for its hot springs, scenic coastline, and proximity to the sacred Nachi Falls and Kumano Nachi Taisha shrine.
E2296655 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: Nachi Katsuura | Statement: [Nachi-no-Hi Matsuri, location, Nachi Katsuura]
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: Nachi Katsuura
Triple: [Nachi-no-Hi Matsuri, location, Nachi Katsuura]
Generated description
Nachi Katsuura is a coastal town in Wakayama Prefecture, Japan, renowned for its hot springs, scenic coastline, and proximity to the sacred Nachi Falls and Kumano Nachi Taisha shrine.

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_69e2953cf6e081909b8e25a10a52dddc completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1cfa267b88190a1e7d599f22441e2 completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a829e17e0c481909f91489ac4013449 completed Aug. 17, 2026, 5:37 a.m.
NEDg Description generation batch_6a829e6945d08190ae56563bf419f409 completed Aug. 17, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_6a829e9301d481908e93f97d3c00747c completed Aug. 17, 2026, 5:39 a.m.
Created at: April 17, 2026, 9:08 p.m.