Triple

T712388
Position Surface form Disambiguated ID Type / Status
Subject ACM SIGGRAPH E14237 entity
Predicate hasRegion P285 FINISHED
Object Asia E2127 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: Asia | Statement: [ACM SIGGRAPH, hasRegion, Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asia
Context triple: [ACM SIGGRAPH, hasRegion, Asia]
  • A. Asia
    Asia is a figure in Greek mythology, often considered an Oceanid nymph associated with the region that later bore her name.
  • B. Asia
    Asia is a figure in Greek mythology, often considered one of the Oceanids and associated with the region that later bore her name.
  • C. Asia chosen
    Asia is the world’s largest and most populous continent, encompassing diverse cultures, languages, and landscapes across the Eastern and Northern Hemispheres.
  • D. Asia-Pacific
    Asia-Pacific is a vast geopolitical and economic region encompassing East Asia, Southeast Asia, Oceania, and surrounding Pacific areas, known for its dynamic economies and strategic global importance.
  • E. East Asia
    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.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a55dd5908190bfb8816f65ea02e1 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6732a8c0881909753261f9256fcf2 completed March 3, 2026, 5:35 a.m.
Created at: March 1, 2026, 7:36 p.m.