Triple

T5501838
Position Surface form Disambiguated ID Type / Status
Subject Sprinter E144345 entity
Predicate safetySystems P23340 FINISHED
Object AWS E86255 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: [Sprinter, safetySystems, AWS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AWS
Context triple: [Sprinter, safetySystems, AWS]
  • A. AWS chosen
    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 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.
  • C. Amazon Web Services
    Amazon Web Services is a leading global cloud computing platform offering on-demand infrastructure, storage, and application services to businesses, developers, and institutions.
  • D. 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.
  • E. Amazon S3
    Amazon S3 is a scalable, highly durable cloud object storage service from Amazon Web Services used for storing and retrieving large amounts of data over the internet.
  • 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_69c008f5a2748190bce7a39aabf87a6d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f0a512c81908f077378917e5879 completed March 22, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027a67d648190ac8d097202c8ec3d completed March 22, 2026, 5:32 p.m.
Created at: March 22, 2026, 3:32 p.m.