Triple

T11062442
Position Surface form Disambiguated ID Type / Status
Subject Tabuelan E261539 entity
Predicate hasLocalLanguage P4185 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: [Tabuelan, hasLocalLanguage, Filipino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filipino
Context triple: [Tabuelan, hasLocalLanguage, 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798eb838c819089a89c55209c0295 completed April 9, 2026, 12:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d6070248190adb8e74daff09f83 completed April 19, 2026, 1:18 a.m.
Created at: April 8, 2026, 9:26 p.m.