Triple

T19803164
Position Surface form Disambiguated ID Type / Status
Subject Emmanuel Pelaez E475737 entity
Predicate nativeLanguage P151 FINISHED
Object Cebuano NE NERFINISHED

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: Cebuano | Statement: [Emmanuel Pelaez, nativeLanguage, Cebuano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cebuano
Context triple: [Emmanuel Pelaez, nativeLanguage, 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. Binisaya
    Binisaya is a major Austronesian language of the Philippines, widely spoken in the Central Visayas and parts of Mindanao.
  • C. Tagalog
    Tagalog is an Austronesian language primarily spoken in the Philippines and serves as the basis for the country’s national language, Filipino.
  • D. Waray language
    Waray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly on Samar and nearby islands.
  • E. Ilocano
    Ilocano refers to a major ethnolinguistic group from the northern Philippines, known for its distinct Ilocano language and rich agricultural and coastal cultural traditions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e654266e18819085698aed8b0e2ba8 completed April 20, 2026, 4:28 p.m.
Created at: April 10, 2026, 1:49 p.m.