Triple

T14231828
Position Surface form Disambiguated ID Type / Status
Subject Kawi E352768 entity
Predicate influenced P9 FINISHED
Object Baybayin E5135 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: Baybayin | Statement: [Kawi, influenced, Baybayin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baybayin
Context triple: [Kawi, influenced, Baybayin]
  • A. Baybayin chosen
    Baybayin is an ancient pre-colonial Philippine script used to write several native languages before the widespread adoption of the Latin alphabet.
  • B. Tagbanwa script
    Tagbanwa script is an indigenous Brahmic-derived writing system historically used by the Tagbanwa people of Palawan in the Philippines to write their native languages.
  • C. Hanunóo script
    The Hanunóo script is an indigenous Brahmic-derived syllabic writing system traditionally used by the Hanunóo Mangyan people of Mindoro in the Philippines.
  • D. Filipino alphabet
    The Filipino alphabet is the standardized set of letters used to write the modern Filipino language and several Philippine regional languages.
  • E. Hanunoo Mangyan
    Hanunoo Mangyan are an indigenous people of the Philippines known for their traditional swidden agriculture, rich oral literature, and unique pre-Hispanic syllabic script.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622cdd6481908befa179a9675bb5 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd281bc67c81909bb09ee4a39a0b7f completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:07 a.m.