Triple

T7983224
Position Surface form Disambiguated ID Type / Status
Subject Hidetoshi Nakata E185623 entity
Predicate familyName P18 FINISHED
Object Nakata
Nakata is a Japanese surname most famously associated with former professional footballer Hidetoshi Nakata, one of Japan’s best-known international players.
 E742751 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: Nakata | Statement: [Hidetoshi Nakata, familyName, Nakata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nakata
Context triple: [Hidetoshi Nakata, familyName, Nakata]
  • A. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • B. Nōgata
    Nōgata is a city in western Japan located in Fukuoka Prefecture on the island of Kyushu.
  • C. Nagahori
    Nagahori is a district in Osaka, Japan, known primarily as an urban area served by the Osaka Metro Nagahori Tsurumi-ryokuchi Line.
  • D. 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.
  • E. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • 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: Nakata
Triple: [Hidetoshi Nakata, familyName, Nakata]
Generated description
Nakata is a Japanese surname most famously associated with former professional footballer Hidetoshi Nakata, one of Japan’s best-known international players.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nakata
Target entity description: Nakata is a Japanese surname most famously associated with former professional footballer Hidetoshi Nakata, one of Japan’s best-known international players.
  • A. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • B. Nōgata
    Nōgata is a city in western Japan located in Fukuoka Prefecture on the island of Kyushu.
  • C. Nagahori
    Nagahori is a district in Osaka, Japan, known primarily as an urban area served by the Osaka Metro Nagahori Tsurumi-ryokuchi Line.
  • D. 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.
  • E. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • 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_69ca829a2cfc819083d591d58ec04075 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c2a1aa881909c3cea280dff38f5 completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce8828faf48190927b2a6680f6b4d8 completed April 2, 2026, 3:15 p.m.
NEDg Description generation batch_69ce8a442b508190bd8319fda51edc4b completed April 2, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_69ce8afff50c8190b2dd1a7e0a5a130b completed April 2, 2026, 3:28 p.m.
Created at: March 30, 2026, 5:15 p.m.