Triple

T6541673
Position Surface form Disambiguated ID Type / Status
Subject Alexa mobile app E168302 entity
Predicate developer P73 FINISHED
Object Amazon E4942 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: Amazon | Statement: [Alexa mobile app, developer, Amazon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon
Context triple: [Alexa mobile app, developer, Amazon]
  • A. Amazon chosen
    Amazon is a multinational technology and e-commerce company best known for its vast online marketplace, cloud computing services through AWS, and significant influence on global retail and logistics.
  • B. Amazon
    Amazon is the small sailing boat featured in Arthur Ransome’s children’s novel "Swallows and Amazons," crewed by the adventurous Blackett sisters.
  • C. Amazon Prime
    Amazon Prime is a subscription service from Amazon that offers members benefits like fast shipping, streaming video and music, and access to exclusive deals.
  • D. Amazon Air
    Amazon Air is the cargo airline division of Amazon that operates a dedicated air network to expedite the company’s package delivery across the United States and internationally.
  • E. Jet.com
    Jet.com was an American e-commerce company known for its dynamic pricing model and rapid growth as a Walmart-acquired online retail platform.
  • 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_69c68a51564081909e93aee0dbd9cca3 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6add9036081908917ff27ceed1038 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d541f25081909a4b218fd38718c6 completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:50 p.m.