Triple
T12323241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Kinesis |
E293770
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Amazon Kinesis Data Analytics |
E426144
|
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 Data Analytics | Statement: [Amazon Kinesis, hasComponent, Amazon Kinesis Data Analytics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon Kinesis Data Analytics Context triple: [Amazon Kinesis, hasComponent, Amazon Kinesis Data Analytics]
-
A.
Amazon Kinesis Data Analytics
chosen
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.
-
B.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
C.
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.
-
D.
Azure Stream Analytics
Azure Stream Analytics is a real-time analytics and complex event processing service in Microsoft Azure that ingests and analyzes streaming data from various sources to generate timely insights and actions.
-
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_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_69f61e8d27288190bdf32acd600141db |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.