Triple

T21396659
Position Surface form Disambiguated ID Type / Status
Subject Iranon E527803 entity
Predicate relatedLanguage P10003 FINISHED
Object Maranao language 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: Maranao language | Statement: [Iranon, relatedLanguage, Maranao language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maranao language
Context triple: [Iranon, relatedLanguage, Maranao language]
  • A. Maranao language chosen
    The Maranao language is an Austronesian language spoken primarily by the Maranao people around Lake Lanao in Mindanao, Philippines.
  • B. Bontoc language
    The Bontoc language is an Austronesian language spoken by the Bontoc people of the Mountain Province in the northern Philippines.
  • C. Maguindanaon language
    The Maguindanaon language is an Austronesian language spoken primarily by the Maguindanaon people in the Mindanao region of the southern Philippines.
  • D. Agusan Manobo language
    Agusan Manobo language is an Austronesian language spoken by the Manobo people of northeastern Mindanao in the Philippines.
  • E. Yakan language
    The Yakan language is an Austronesian language spoken primarily by the Yakan people of the Sulu Archipelago and nearby areas in the southern Philippines.
  • 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_69e0b51ff3748190935c0a513c62a12b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b11a2aec8190a60e53b90d0823b1 completed April 22, 2026, 11:29 a.m.
Created at: April 16, 2026, 5:13 p.m.