Triple

T7799530
Position Surface form Disambiguated ID Type / Status
Subject Hermann Roesler E180391 entity
Predicate languageSpoken P151 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: [Hermann Roesler, languageSpoken, Japanese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japanese
Context triple: [Hermann Roesler, languageSpoken, 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_69ca827e50cc8190a92a733577184938 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae985d8f08190b38d9d6848a7dc83 completed March 30, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb142117b48190bdc17677592bfa8f completed March 31, 2026, 12:24 a.m.
Created at: March 30, 2026, 4:32 p.m.