Triple

T12321994
Position Surface form Disambiguated ID Type / Status
Subject AWS Lambda E293752 entity
Predicate supportsTrigger P36418 FINISHED
Object Amazon DynamoDB Streams E427710 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 DynamoDB Streams | Statement: [AWS Lambda, supportsTrigger, Amazon DynamoDB Streams]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon DynamoDB Streams
Context triple: [AWS Lambda, supportsTrigger, Amazon DynamoDB Streams]
  • A. DynamoDB Streams chosen
    DynamoDB Streams is a change data capture feature of Amazon DynamoDB that records item-level modifications in near real time for use cases like event-driven processing, replication, and auditing.
  • B. 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.
  • C. Amazon Kinesis
    Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
  • D. Amazon DocumentDB
    Amazon DocumentDB is a fully managed, scalable document database service from AWS designed to be compatible with MongoDB workloads and optimized for performance, durability, and security in the cloud.
  • E. Amazon Kinesis Data Firehose
    Amazon Kinesis Data Firehose is a fully managed AWS service for reliably capturing, transforming, and loading real-time streaming data into data lakes, warehouses, and analytics services.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f4d7dac81909ff10e64e229ef33 completed April 10, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e8aa94881908e4c184062037ab5 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:53 p.m.