Triple

T4914686
Position Surface form Disambiguated ID Type / Status
Subject Taobao E110317 entity
Predicate competitor P1375 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: [Taobao, competitor, Amazon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon
Context triple: [Taobao, competitor, 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 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.
  • C. 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.
  • D. Best Buy
    Best Buy is a major American consumer electronics retail chain known for selling computers, appliances, and entertainment products through large-format stores and online.
  • E. Kogan
    Kogan is a variant form of the Jewish surname Cohen, often arising from transliteration or regional spelling differences.
  • 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_69bd44132b94819088522d92beaadc78 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e9f12b48190b3cb5378958d03cd completed March 20, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6feaf3dc81908b2c7a7409b1c952 completed March 21, 2026, 10:16 a.m.
Created at: March 20, 2026, 1:29 p.m.