Triple

T356994
Position Surface form Disambiguated ID Type / Status
Subject Cebuano language E7565 entity
Predicate hasDialect P4251 FINISHED
Object Urban Cebuano E7565 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: Urban Cebuano | Statement: [Cebuano language, hasDialect, Urban Cebuano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urban Cebuano
Context triple: [Cebuano language, hasDialect, Urban Cebuano]
  • A. Cebuano language chosen
    The Cebuano language is an Austronesian language widely spoken in the southern Philippines, particularly in the Visayas and parts of Mindanao.
  • B. Kapampangan language
    Kapampangan is an Austronesian language of the Philippines primarily spoken in the Pampanga region of Central Luzon.
  • C. Bikol language
    The Bikol language is an Austronesian language spoken primarily in the Bicol Region of the Philippines, known for its several regional varieties and close relation to other Central Philippine languages.
  • D. Tagalog
    Tagalog is an Austronesian language primarily spoken in the Philippines and serves as the basis for the country’s national language, Filipino.
  • E. Ilocano language
    The Ilocano language is an Austronesian language widely spoken in northern Luzon and by migrant communities across the Philippines and abroad.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebaf0c9881909313f98818e7fa58 completed Feb. 28, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e57647d481908d42b10ddebf3ff7 completed March 1, 2026, 7:06 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.