Triple

T8667974
Position Surface form Disambiguated ID Type / Status
Subject Voyager trains E205721 entity
Predicate safetySystem P840 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: [Voyager trains, safetySystem, AWS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AWS
Context triple: [Voyager trains, safetySystem, 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 (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
    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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48a48b548190b78259072b1224ee completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecd1ca88c8190a3b2ca79a7204248 completed April 2, 2026, 8:10 p.m.
Created at: March 30, 2026, 6:31 p.m.