Triple
T18800852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS CDK |
E459748
|
entity |
| Predicate | supportsService |
P203
|
FINISHED |
| Object |
AWS Glue DataBrew
AWS Glue DataBrew is a visual data preparation service that lets users clean, normalize, and transform data without writing code, integrating with various AWS analytics and storage services.
|
E97123
|
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: AWS Glue DataBrew | Statement: [AWS CDK, supportsService, AWS Glue DataBrew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AWS Glue DataBrew Context triple: [AWS CDK, supportsService, AWS Glue DataBrew]
-
A.
AWS Glue
AWS Glue is a fully managed extract, transform, and load (ETL) service from Amazon Web Services that simplifies data preparation and integration for analytics and data warehousing.
-
B.
Amazon Athena
Amazon Athena is a serverless, interactive query service from AWS that lets users analyze data directly in Amazon S3 using standard SQL.
-
C.
AWS Lake Formation
AWS Lake Formation is a managed AWS service that simplifies building, securing, and managing data lakes by centralizing data access control and governance across analytics services.
-
D.
Amazon QuickSight
Amazon QuickSight is a cloud-based business intelligence and data visualization service from AWS that enables users to create interactive dashboards and insights from various data sources.
-
E.
Amazon SageMaker
Amazon SageMaker is a fully managed cloud service that enables developers and data scientists to build, train, and deploy machine learning models at scale.
- 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: AWS Glue DataBrew Triple: [AWS CDK, supportsService, AWS Glue DataBrew]
Generated description
AWS Glue DataBrew is a visual data preparation service that lets users clean, normalize, and transform data without writing code, integrating with various AWS analytics and storage services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AWS Glue DataBrew Target entity description: AWS Glue DataBrew is a visual data preparation service that lets users clean, normalize, and transform data without writing code, integrating with various AWS analytics and storage services.
-
A.
AWS Glue
chosen
AWS Glue is a fully managed extract, transform, and load (ETL) service from Amazon Web Services that simplifies data preparation and integration for analytics and data warehousing.
-
B.
Amazon Athena
Amazon Athena is a serverless, interactive query service from AWS that lets users analyze data directly in Amazon S3 using standard SQL.
-
C.
AWS Lake Formation
AWS Lake Formation is a managed AWS service that simplifies building, securing, and managing data lakes by centralizing data access control and governance across analytics services.
-
D.
Amazon QuickSight
Amazon QuickSight is a cloud-based business intelligence and data visualization service from AWS that enables users to create interactive dashboards and insights from various data sources.
-
E.
Amazon SageMaker
Amazon SageMaker is a fully managed cloud service that enables developers and data scientists to build, train, and deploy machine learning models at scale.
- F. None of above.
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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02332d88190b68feea7f2f86d06 |
completed | April 20, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05675ff6e88190abfa88e1085873f4 |
completed | May 14, 2026, 6:10 a.m. |
| NEDg | Description generation | batch_6a05709c4e388190a451b7b5d6195934 |
completed | May 14, 2026, 6:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05716e0e888190a1e41d5cb2f860bd |
completed | May 14, 2026, 6:53 a.m. |
Created at: April 10, 2026, 11:53 a.m.