Triple

T262086
Position Surface form Disambiguated ID Type / Status
Subject China E5561 entity
Predicate subregion P747 FINISHED
Object East Asia E3827 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: East Asia | Statement: [China, subregion, East Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: East Asia
Context triple: [China, subregion, East Asia]
  • A. East Asia chosen
    East Asia is a subregion of Asia encompassing countries such as China, Japan, and Korea, known for its dense populations, advanced economies, and influential cultures.
  • B. Asia
    Asia is the world’s largest and most populous continent, encompassing diverse cultures, languages, and landscapes across the Eastern and Northern Hemispheres.
  • C. Asia
    Asia is a figure in Greek mythology, often considered an Oceanid nymph associated with the region that later bore her name.
  • D. Asia
    Asia is a figure in Greek mythology, often considered one of the Oceanids and associated with the region that later bore her name.
  • E. North Asia
    North Asia is the vast, sparsely populated northern part of the Asian continent, dominated by Siberia and characterized by its cold climate and extensive forests and tundra.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a42a101a908190808a4e10871b357d completed March 1, 2026, 11:59 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.