Triple

T33105099
Position Surface form Disambiguated ID Type / Status
Subject 中村 E847167 entity
Predicate hasReadingKana P204194 FINISHED
Object なかむら
「なかむら」は、日本で一般的な姓「中村」のかな表記です。
 E2036195 NE FINISHED

How this triple was built (3 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: なかむら | Statement: [中村, hasReadingKana, なかむら]
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: なかむら
Triple: [中村, hasReadingKana, なかむら]
Generated description
「なかむら」は、日本で一般的な姓「中村」のかな表記です。
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasReadingKana
Context triple: [中村, hasReadingKana, なかむら]
  • A. hasKanjiReading
    Indicates that a written kanji character is associated with a specific reading or pronunciation.
  • B. hasHokkienReading
    Indicates that an entity is associated with a specific reading or pronunciation in the Hokkien language.
  • C. hasMandarinReading
    Indicates that an entity is associated with a specific reading or pronunciation in Mandarin Chinese.
  • D. hasReading
    Indicates that an entity is associated with a particular reading, such as a measured value, interpretation, or recorded observation.
  • E. japaneseOnReading
    Indicates the on-yomi (Sino-Japanese) pronunciation associated with a given Japanese kanji or term.
  • F. None of above. chosen

Provenance (7 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_69f3495686508190b76bf20fa5e00bf7 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_6a03460f3a8c8190ae3f4cd69e0e54d9 completed May 12, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a34f0313d508190b1c8f714daffbb50 completed June 19, 2026, 7:30 a.m.
NEDg Description generation batch_6a34f3b48d6c8190a95aebe113e72028 completed June 19, 2026, 7:45 a.m.
NED2 Entity disambiguation (via description) batch_6a34f43667e481909d14bd45b744a85f completed June 19, 2026, 7:48 a.m.
PD Predicate disambiguation batch_6a0345810b3481908aec06ab2b712e12 completed May 12, 2026, 3:21 p.m.
PDg Predicate description generation batch_6a03460e44cc8190b1ac3e8ac0840a52 completed May 12, 2026, 3:23 p.m.
Created at: May 1, 2026, 1:26 a.m.