Triple

T8425223
Position Surface form Disambiguated ID Type / Status
Subject Bebot E198966 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: [Bebot, language, Tagalog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tagalog
Context triple: [Bebot, 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. Philippine English
    Philippine English is the localized variety of English used in the Philippines, shaped by American English influence and Philippine languages in its vocabulary, pronunciation, and usage.
  • 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_69ca8312d63c8190bf133b676b44a385 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb85a2871081908a4093838fc93b5a completed March 31, 2026, 8:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce0364f294819091ef9f39429f3fb5 completed April 2, 2026, 5:49 a.m.
Created at: March 30, 2026, 6:07 p.m.