Triple

T16169597
Position Surface form Disambiguated ID Type / Status
Subject McCann Erickson E392398 entity
Predicate hasOfficeIn P1268 FINISHED
Object Asia-Pacific E5562 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-Pacific | Statement: [McCann Erickson, hasOfficeIn, Asia-Pacific]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asia-Pacific
Context triple: [McCann Erickson, hasOfficeIn, Asia-Pacific]
  • A. Asia-Pacific chosen
    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.
  • B. 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."
  • C. Asia
    Asia is a figure in Greek mythology, often considered an Oceanid nymph associated with the region that later bore her name.
  • D. Asia
    Asia is a figure in Greek mythology, often considered one of the Oceanids and associated with the region that later bore her name.
  • E. Asia
    Asia is the world’s largest and most populous continent, encompassing diverse cultures, languages, and landscapes across the Eastern and Northern Hemispheres.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21eb5e6d881908749683091afa90c completed April 17, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000ec9ab2c819098d96dae98f78f50 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:02 a.m.