Triple

T13070133
Position Surface form Disambiguated ID Type / Status
Subject Anpanman picture books E329433 entity
Predicate featureCharacter P23263 FINISHED
Object Dokin-chan E1020413 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: Dokin-chan | Statement: [Anpanman picture books, featureCharacter, Dokin-chan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dokin-chan
Context triple: [Anpanman picture books, featureCharacter, Dokin-chan]
  • A. Dokin-chan chosen
    Dokin-chan is a mischievous yet charming character from the Japanese children's anime "Anpanman," often depicted as Baikinman's companion with a crush on Shokupanman.
  • B. Shoki
    "Shoki" is a popular Nigerian street-hop song by Lil Kesh that helped propel him to mainstream fame and popularized a viral dance of the same name.
  • C. Tajōmaru
    Tajōmaru is the notorious bandit whose conflicting testimonies drive the plot and themes of truth and perception in Ryūnosuke Akutagawa’s short story "In a Grove."
  • D. Hozuki-ichi
    Hozuki-ichi is a traditional summer fair in Asakusa, Tokyo, known for its stalls selling bright orange hōzuki (ground cherry) plants and its association with visits to Senso-ji Temple.
  • E. Dokki
    Dokki is a prominent district in Giza, Egypt, known for its government institutions, educational centers, and residential neighborhoods just across the Nile from central Cairo.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ee6130819095d835e7ff6a8c5b completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e26e5d6881908663444bca67b01e completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9 p.m.