Triple

T8093932
Position Surface form Disambiguated ID Type / Status
Subject Apache Flink E188935 entity
Predicate integratesWith P1075 FINISHED
Object Amazon Kinesis E293770 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 Kinesis | Statement: [Apache Flink, integratesWith, Amazon Kinesis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon Kinesis
Context triple: [Apache Flink, integratesWith, Amazon Kinesis]
  • A. Amazon Kinesis chosen
    Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
  • B. 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.
  • C. Amazon Kinesis Data Analytics
    Amazon Kinesis Data Analytics is a fully managed AWS service that enables real-time processing and analysis of streaming data using SQL or Apache Flink.
  • D. Amazon EventBridge
    Amazon EventBridge is a serverless event bus service from AWS that enables applications to connect using events from AWS services, integrated SaaS applications, and custom sources for event-driven architectures.
  • E. Amazon EMR
    Amazon EMR is a managed big data platform on AWS that simplifies running large-scale data processing frameworks like Apache Hadoop and Spark on elastic cloud clusters.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc64112138819096050975d707d8ee completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:30 p.m.