Triple

T7334741
Position Surface form Disambiguated ID Type / Status
Subject Middle East and Africa E169098 entity
Predicate continentPart P17379 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: [Middle East and Africa, continentPart, Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asia
Context triple: [Middle East and Africa, continentPart, 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
    Asia is a British rock supergroup formed in the early 1980s, known for its melodic progressive rock sound and hits like "Heat of the Moment."
  • D. Asia chosen
    Asia is the world’s largest and most populous continent, encompassing diverse cultures, languages, and landscapes across the Eastern and Northern Hemispheres.
  • E. Asianet
    Asianet is a leading Malayalam-language television channel and entertainment network widely watched in the Indian state of Kerala and among the Malayali diaspora.
  • 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_69c68a568a6481908f11e20db7bc8446 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0c25758819095aa5041c6ecff07 completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c810cbd78c8190934dd5d4baa1a0a7 completed March 28, 2026, 5:33 p.m.
Created at: March 27, 2026, 3:04 p.m.