Triple

T1603667
Position Surface form Disambiguated ID Type / Status
Subject Hakka E34449 entity
Predicate hasDialect P4251 FINISHED
Object Dabu Hakka E34449 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: Dabu Hakka | Statement: [Hakka, hasDialect, Dabu Hakka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dabu Hakka
Context triple: [Hakka, hasDialect, Dabu Hakka]
  • A. Hakka chosen
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • B. Honancho
    Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
  • C. Kaiyukan
    Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
  • D. Gamosa
    Gamosa is a traditional Assamese handwoven cotton cloth, typically white with red borders and motifs, symbolizing respect, cultural identity, and social bonding in Assam.
  • E. Habikino
    Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
  • 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_69a885fea6a481909fe83ba6441f1774 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9094f96ec819090286c21b3dfddd5 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad46ae8ef08190acf018f1db4bfa7c completed March 8, 2026, 9:51 a.m.
Created at: March 4, 2026, 7:28 p.m.