Triple

T4600405
Position Surface form Disambiguated ID Type / Status
Subject Amazon S3 E100305 entity
Predicate integratesWith P1075 FINISHED
Object Amazon RDS E97121 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 RDS | Statement: [Amazon S3, integratesWith, Amazon RDS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon RDS
Context triple: [Amazon S3, integratesWith, Amazon RDS]
  • A. Amazon RDS chosen
    Amazon RDS is a managed relational database service by Amazon Web Services that simplifies setup, operation, and scaling of databases in the cloud.
  • B. Amazon Aurora
    Amazon Aurora is a fully managed, cloud-native relational database engine from AWS designed for high performance, scalability, and compatibility with MySQL and PostgreSQL.
  • C. Amazon Redshift
    Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
  • D. Amazon DynamoDB
    Amazon DynamoDB is a fully managed, serverless NoSQL database service by AWS designed for high-performance, scalable key-value and document data storage.
  • E. AWS Database Migration Service
    AWS Database Migration Service is a managed cloud service that helps you securely and reliably migrate and replicate databases to AWS with minimal downtime.
  • 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_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5971f448819090f6e76c7d3ffc2d completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa5a7aac8190b540b80816d55051 completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.