Triple

T16852911
Position Surface form Disambiguated ID Type / Status
Subject Hisense (selected models) E409717 entity
Predicate marketRegion P12320 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: [Hisense (selected models), marketRegion, Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asia
Context triple: [Hisense (selected models), marketRegion, 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b37abadc81909d02d329403497d6 completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c79e86ac8190b89c4ebb05250b4f completed May 10, 2026, 5:59 p.m.
Created at: April 10, 2026, 5:24 a.m.