Triple

T6496570
Position Surface form Disambiguated ID Type / Status
Subject Franciscan missions E148174 entity
Predicate geographicRegion 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: [Franciscan missions, geographicRegion, Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asia
Context triple: [Franciscan missions, geographicRegion, 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06aba8f04819080b291baf79c42d5 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c66376b63081909fefd93790fa4b55 completed March 27, 2026, 11:01 a.m.
Created at: March 22, 2026, 4:53 p.m.