Triple

T21997478
Position Surface form Disambiguated ID Type / Status
Subject PASAI E543242 entity
Predicate acronym P43 FINISHED
Object PASAI 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: PASAI | Statement: [PASAI, acronym, PASAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PASAI
Context triple: [PASAI, acronym, PASAI]
  • A. PASAI chosen
    PASAI is the regional organization of Supreme Audit Institutions for the Pacific, supporting public sector auditing and accountability across Pacific Island countries.
  • B. PASAKA
    PASAKA is a political organization representing and advocating for the rights and interests of the Lumad indigenous peoples in the Philippines.
  • C. Pasil
    Pasil is a rural municipality in the mountainous province of Kalinga in the Philippines, known for its indigenous communities and rice-terraced landscapes.
  • D. Sak Pase
    Sak Pase is a music producer best known for his work in hip-hop and pop, including collaborations with major artists like Jay-Z and Kanye West.
  • E. PASA
    PASA is a peer-reviewed scientific journal that publishes research in astronomy and astrophysics on behalf of the Astronomical Society of Australia.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276774508190b96870266e10979a completed April 28, 2026, 9:32 p.m.
Created at: April 16, 2026, 8:19 p.m.