Triple

T9838332
Position Surface form Disambiguated ID Type / Status
Subject Deeplearning.ai E239157 entity
Predicate collaboratesWith P37 FINISHED
Object AWS E59926 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: AWS | Statement: [Deeplearning.ai, collaboratesWith, AWS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AWS
Context triple: [Deeplearning.ai, collaboratesWith, AWS]
  • A. AWS
    AWS is a train protection and warning system used on railways to alert drivers to signal aspects and speed restrictions, enhancing operational safety.
  • B. AWS
    AWS (Solidarity Electoral Action) was a Polish political coalition formed in the early 1990s that brought together post-Solidarity groups to contest democratic elections after the fall of communism.
  • C. Aws
    Aws was one of the major Arab tribes of Medina that played a pivotal role in supporting Prophet Muhammad and the early Muslim community after the Hijrah.
  • D. Amazon Web Services chosen
    Amazon Web Services is a leading global cloud computing platform offering on-demand infrastructure, storage, and application services to businesses, developers, and institutions.
  • E. Azure
    Azure is Microsoft's cloud computing platform offering a wide range of services for building, deploying, and managing applications and infrastructure through Microsoft-managed data centers.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34921b881909836ba0f5b42a27b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5d145ac8190ad10a4328216ef54 completed April 5, 2026, 3:24 a.m.
Created at: March 30, 2026, 8:33 p.m.