Triple

T15468074
Position Surface form Disambiguated ID Type / Status
Subject Nikai school E372082 entity
Predicate namedAfter P63 FINISHED
Object Nikai
Nikai is the namesake of the Nikai school, likely a person of significance such as a founder, benefactor, or notable figure associated with the institution.
 E1158664 NE FINISHED

How this triple was built (4 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: Nikai | Statement: [Nikai school, namedAfter, Nikai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nikai
Context triple: [Nikai school, namedAfter, Nikai]
  • A. Nikaho
    Nikaho is a coastal city in northern Japan known for its scenic Sea of Japan shoreline and location in southwestern Akita Prefecture.
  • B. Nakanai
    Nakanai is an Austronesian language spoken on the island of New Britain in Papua New Guinea, known for its role in the linguistic diversity of the Bismarck Archipelago.
  • C. Nakata
    Nakata is a Japanese surname most famously associated with former professional footballer Hidetoshi Nakata, one of Japan’s best-known international players.
  • D. Norikura
    Norikura is a ski resort area in Japan’s Hakuba Valley, known for its scenic alpine terrain and winter sports opportunities.
  • E. Nishiizu
    Nishiizu is a coastal town in Shizuoka Prefecture, Japan, known for its rugged seaside scenery, hot springs, and views of Suruga Bay.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Nikai
Triple: [Nikai school, namedAfter, Nikai]
Generated description
Nikai is the namesake of the Nikai school, likely a person of significance such as a founder, benefactor, or notable figure associated with the institution.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nikai
Target entity description: Nikai is the namesake of the Nikai school, likely a person of significance such as a founder, benefactor, or notable figure associated with the institution.
  • A. Nikaho
    Nikaho is a coastal city in northern Japan known for its scenic Sea of Japan shoreline and location in southwestern Akita Prefecture.
  • B. Nakanai
    Nakanai is an Austronesian language spoken on the island of New Britain in Papua New Guinea, known for its role in the linguistic diversity of the Bismarck Archipelago.
  • C. Nakata
    Nakata is a Japanese surname most famously associated with former professional footballer Hidetoshi Nakata, one of Japan’s best-known international players.
  • D. Norikura
    Norikura is a ski resort area in Japan’s Hakuba Valley, known for its scenic alpine terrain and winter sports opportunities.
  • E. Nishiizu
    Nishiizu is a coastal town in Shizuoka Prefecture, Japan, known for its rugged seaside scenery, hot springs, and views of Suruga Bay.
  • F. None of above. chosen

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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f69a31c81909a749247b6615d91 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d03845c8190bc8cb96827a5da39 completed May 9, 2026, 12:48 p.m.
NEDg Description generation batch_69ff2e2fb3e48190b2274d54586b1f00 completed May 9, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_69ff2ec231dc8190b82333e3e54ced20 completed May 9, 2026, 12:55 p.m.
Created at: April 10, 2026, 3:33 a.m.