Triple

T22134584
Position Surface form Disambiguated ID Type / Status
Subject Java E546991 entity
Predicate languageSpoken P151 FINISHED
Object Betawi 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: Betawi | Statement: [Java, languageSpoken, Betawi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Betawi
Context triple: [Java, languageSpoken, Betawi]
  • A. Betawi chosen
    Betawi is an Austronesian language spoken primarily by the Betawi people in and around Jakarta, Indonesia, and is closely associated with the city's urban culture and history.
  • B. Jatinegara
    Jatinegara is a district in East Jakarta, Indonesia, known as a densely populated urban area with significant transportation hubs and historical sites.
  • C. Bidayuh
    Bidayuh is an indigenous ethnic group of Borneo, primarily in Sarawak, Malaysia, known for its distinct languages, traditional longhouse culture, and rich agricultural and ritual practices.
  • D. Nai Abadi
    Nai Abadi is a residential neighborhood located within the town of SITE.
  • E. Cilandak
    Cilandak is a district in South Jakarta, Indonesia, known as a primarily residential and commercial area with several educational institutions and office complexes.
  • 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_69e11e39bf348190b541bfa16a7b71e0 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129b8f4248190b6342c8d00942c25 completed April 28, 2026, 9:42 p.m.
Created at: April 16, 2026, 8:32 p.m.