Triple

T21495856
Position Surface form Disambiguated ID Type / Status
Subject Kanai E530349 entity
Predicate languageUsed P238 FINISHED
Object Japanese NE NERFINISHED

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 | Statement: [Kanai, languageUsed, Japanese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japanese
Context triple: [Kanai, languageUsed, Japanese]
  • A. Japanese chosen
    Japanese is the national language of Japan, a Japonic language known for its complex writing system combining kanji and kana.
  • B. Yapese
    Yapese is an Austronesian language spoken primarily on the island of Yap and nearby islands in the western Pacific.
  • C. JPN
    JPN is the official FIFA trigramme used to represent the Japan women's national football team in international competitions and records.
  • D. Japanese cuisine
    Japanese cuisine is a culinary tradition known for its emphasis on seasonal ingredients, refined presentation, and dishes such as sushi, tempura, ramen, and kaiseki.
  • E. JP
    JP is the official Indian Railways station code for Jaipur Junction, a major railway hub in the city of Jaipur, Rajasthan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45bd15481909fba5910765cdda2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea582d9c8190b95ff6e1b8179b81 completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:23 p.m.