Triple

T762386
Position Surface form Disambiguated ID Type / Status
Subject Mactan E16099 entity
Predicate country P26 FINISHED
Object Philippines E2051 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: Philippines | Statement: [Mactan, country, Philippines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippines
Context triple: [Mactan, country, Philippines]
  • A. Philippines chosen
    The Philippines is a Southeast Asian archipelagic country in the western Pacific Ocean known for its diverse culture, colonial history, and thousands of islands.
  • B. Luzon
    Luzon is the largest and most populous island in the Philippines, home to the nation’s capital, Manila, and its main political and economic centers.
  • C. Palau
    Palau is a small island country in the western Pacific Ocean known for its rich marine biodiversity, pristine coral reefs, and status as a popular diving destination.
  • D. Philippine Archipelago
    The Philippine Archipelago is a vast group of over 7,000 tropical islands in Southeast Asia, known for its rich biodiversity, complex geology, and location along the Pacific Ring of Fire.
  • E. Indonesia
    Indonesia is a large Southeast Asian nation made up of thousands of islands, known for its diverse cultures, significant natural resources, and status as one of the world’s largest emerging economies.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a6841f388190a6d08c3bf5c17fe4 completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e426adc8190b7fa65aeacf8737f completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:37 p.m.