Triple

T6513166
Position Surface form Disambiguated ID Type / Status
Subject Sojin E148185 entity
Predicate usedInLanguage P907 FINISHED
Object Japanese language E4278 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: Japanese language | Statement: [Sojin, usedInLanguage, Japanese language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japanese language
Context triple: [Sojin, usedInLanguage, Japanese language]
  • A. The Japanese Language
    The Japanese Language is a comprehensive scholarly work by linguist Roy Andrew Miller that examines the history, structure, and classification of the Japanese language within East Asian linguistics.
  • B. Japanese chosen
    Japanese is the national language of Japan, a Japonic language known for its complex writing system combining kanji and kana.
  • C. Yapese
    Yapese is an Austronesian language spoken primarily on the island of Yap and nearby islands in the western Pacific.
  • D. JPN
    JPN is the official FIFA trigramme used to represent the Japan women's national football team in international competitions and records.
  • E. Japonic languages
    The Japonic languages are a small language family that includes Japanese and the Ryukyuan languages, spoken primarily in Japan and the Ryukyu Islands of East Asia.
  • 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_69c687e68e748190baceb9298f32d3ed completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69f3db330819092503af4fb0649ea completed March 27, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb69ca0c8190954dbe6c627981f3 completed March 27, 2026, 6:24 p.m.
Created at: March 27, 2026, 1:44 p.m.