Triple

T9814758
Position Surface form Disambiguated ID Type / Status
Subject Akihabara Station E238372 entity
Predicate hasLanguage P15 FINISHED
Object Japanese 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 | Statement: [Akihabara Station, hasLanguage, Japanese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japanese
Context triple: [Akihabara Station, hasLanguage, 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. JP
    JP is the popular abbreviation for Jayaprakash Narayan, an Indian independence activist and political leader known for spearheading the 1970s "Total Revolution" movement against corruption and authoritarianism.
  • E. JP
    JP is the two-letter IATA airline designator that was assigned to the former Slovenian national carrier Adria Airways.
  • 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f19660819083e3f15780352052 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc67db68819093217c9a74e72fbf completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:30 p.m.