Triple

T16217376
Position Surface form Disambiguated ID Type / Status
Subject PAGASA E393628 entity
Predicate shortName P43 FINISHED
Object PAGASA E393628 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: PAGASA | Statement: [PAGASA, shortName, PAGASA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PAGASA
Context triple: [PAGASA, shortName, PAGASA]
  • A. PAGASA chosen
    PAGASA is the Philippine government’s national meteorological and hydrological agency responsible for weather forecasting, flood warnings, and related atmospheric services.
  • B. Arambol
    Arambol is a popular coastal village in North Goa, India, known for its scenic beach, relaxed atmosphere, and vibrant backpacker and alternative music scene.
  • C. Typhoon
    Typhoon is the NATO reporting name for the Soviet/Russian Project 941 class of massive nuclear-powered ballistic missile submarines, among the largest submarines ever built.
  • D. Typhoon
    "Typhoon" is a novella by Joseph Conrad that vividly portrays a steamship captain and his crew battling a violent storm at sea, exploring themes of duty, endurance, and human insignificance before nature.
  • E. Typhoon Haiyan
    Typhoon Haiyan was one of the strongest and deadliest tropical cyclones ever recorded, devastating large parts of the Philippines and surrounding regions in November 2013.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e227f76f748190831d230d32c18611 completed April 17, 2026, 12:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000796bc5c81909d2acb68851c9bb8 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:03 a.m.