Triple
T12322010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS Lambda |
E293752
|
entity |
| Predicate | supportsTrigger |
P36418
|
FINISHED |
| Object |
Amazon MSK
Amazon MSK is a fully managed Apache Kafka service from AWS that simplifies setting up, scaling, and operating Kafka clusters for streaming data applications.
|
E974440
|
NE FINISHED |
How this triple was built (4 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 MSK | Statement: [AWS Lambda, supportsTrigger, Amazon MSK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon MSK Context triple: [AWS Lambda, supportsTrigger, Amazon MSK]
-
A.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
B.
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.
-
C.
Amazon MQ
Amazon MQ is a managed message broker service that simplifies setting up and operating popular open-source message brokers like Apache ActiveMQ and RabbitMQ in the cloud.
-
D.
Amazon Elastic Kubernetes Service
Amazon Elastic Kubernetes Service (Amazon EKS) is a cloud-based, fully managed service from AWS for running and scaling containerized applications using Kubernetes.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Amazon MSK Triple: [AWS Lambda, supportsTrigger, Amazon MSK]
Generated description
Amazon MSK is a fully managed Apache Kafka service from AWS that simplifies setting up, scaling, and operating Kafka clusters for streaming data applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amazon MSK Target entity description: Amazon MSK is a fully managed Apache Kafka service from AWS that simplifies setting up, scaling, and operating Kafka clusters for streaming data applications.
-
A.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
B.
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.
-
C.
Amazon MQ
Amazon MQ is a managed message broker service that simplifies setting up and operating popular open-source message brokers like Apache ActiveMQ and RabbitMQ in the cloud.
-
D.
Amazon Elastic Kubernetes Service
Amazon Elastic Kubernetes Service (Amazon EKS) is a cloud-based, fully managed service from AWS for running and scaling containerized applications using Kubernetes.
-
E.
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.
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69f61f5e20cc8190a84f50ddded76974 |
completed | May 2, 2026, 3:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6203ef5008190af9103460b096cff |
completed | May 2, 2026, 4:03 p.m. |
Created at: April 8, 2026, 9:53 p.m.