Triple

T441622
Position Surface form Disambiguated ID Type / Status
Subject .phl E10124 entity
Predicate associatedWithCountry P835 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: [.phl, associatedWithCountry, Philippines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philippines
Context triple: [.phl, associatedWithCountry, 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. 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.
  • E. Malaysia
    Malaysia is a Southeast Asian country on the Malay Peninsula and parts of Borneo, known for its multicultural society, tropical rainforests, and rapidly developing economy.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef42b4008190abed9d79926c7022 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a43e706fd8819082dd795fcad5465c completed March 1, 2026, 1:26 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.