Triple

T12130451
Position Surface form Disambiguated ID Type / Status
Subject Aurora Aragon Quezon E288920 entity
Predicate officeContinent P8233 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: [Aurora Aragon Quezon, officeContinent, Asia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asia
Context triple: [Aurora Aragon Quezon, officeContinent, 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158a2c2c8190aaff9d0cce177565 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f642801881909a94d67c99bfd110 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:49 p.m.