Triple

T9342305
Position Surface form Disambiguated ID Type / Status
Subject Dave Bautista E224791 entity
Predicate ethnicOrigin P194 FINISHED
Object Filipino E1182 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: Filipino | Statement: [Dave Bautista, ethnicOrigin, Filipino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filipino
Context triple: [Dave Bautista, ethnicOrigin, Filipino]
  • A. Filipino chosen
    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.
  • B. Tagalog
    Tagalog is an Austronesian language primarily spoken in the Philippines and serves as the basis for the country’s national language, Filipino.
  • C. Zamboangueño
    Zamboangueño is a major variety of the Spanish-based creole language Chavacano spoken primarily in Zamboanga City in the southern Philippines.
  • D. Kapampangan language
    Kapampangan is an Austronesian language of the Philippines primarily spoken in the Pampanga region of Central Luzon.
  • E. Filipina
    Filipina is an island country in Southeast Asia composed of thousands of islands, known for its diverse cultures, tropical landscapes, and strategic location in the western Pacific Ocean.
  • 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_69ca842993248190a79ab06968994b86 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4bb11cd08190b159a6066dd0ebf1 completed April 1, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e4043e288190b05511d537b1614d completed April 4, 2026, 10:12 a.m.
Created at: March 30, 2026, 7:40 p.m.