Triple

T496597
Position Surface form Disambiguated ID Type / Status
Subject Asian New Zealander E10306 entity
Predicate language P15 FINISHED
Object Tagalog E5261 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: Tagalog | Statement: [Asian New Zealander, language, Tagalog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tagalog
Context triple: [Asian New Zealander, language, Tagalog]
  • A. Tagalog chosen
    Tagalog is an Austronesian language primarily spoken in the Philippines and serves as the basis for the country’s national language, Filipino.
  • B. Filipino
    Filipinos are a Southeast Asian ethnolinguistic group native to the Philippines, known for their diverse Austronesian, Spanish, American, and Chinese cultural influences and a global diaspora.
  • C. Kapampangan language
    Kapampangan is an Austronesian language of the Philippines primarily spoken in the Pampanga region of Central Luzon.
  • D. Binisaya
    Binisaya is a major Austronesian language of the Philippines, widely spoken in the Central Visayas and parts of Mindanao.
  • E. 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.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f116f1b4819082f88d6c747368ae completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a481ee2e348190b26b02990b4fb866 completed March 1, 2026, 6:14 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.