Triple
T19749988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AnalyticDB |
E474349
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Alibaba Cloud DataWorks |
—
|
NE NERFINISHED |
How this triple was built (3 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: Alibaba Cloud DataWorks | Statement: [AnalyticDB, integratesWith, Alibaba Cloud DataWorks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alibaba Cloud DataWorks Context triple: [AnalyticDB, integratesWith, Alibaba Cloud DataWorks]
-
A.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
B.
Azure Data Factory
Azure Data Factory is a cloud-based data integration service from Microsoft that enables users to create, schedule, and orchestrate data pipelines for moving and transforming data at scale across diverse sources.
-
C.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
D.
AnalyticDB
AnalyticDB is Alibaba Cloud’s distributed cloud-native data warehousing and analytics service designed for high-performance, real-time analysis of large-scale data.
-
E.
Alibaba Cloud
Alibaba Cloud is a leading global cloud computing and infrastructure services provider originating from China, offering a wide range of scalable computing, storage, and data solutions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alibaba Cloud DataWorks Target entity description: Alibaba Cloud DataWorks is a fully managed, cloud-native data integration, development, and governance platform that supports building and orchestrating complex data pipelines and analytics workflows on Alibaba Cloud.
-
A.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
B.
Azure Data Factory
Azure Data Factory is a cloud-based data integration service from Microsoft that enables users to create, schedule, and orchestrate data pipelines for moving and transforming data at scale across diverse sources.
-
C.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
D.
AnalyticDB
AnalyticDB is Alibaba Cloud’s distributed cloud-native data warehousing and analytics service designed for high-performance, real-time analysis of large-scale data.
-
E.
Alibaba Cloud
Alibaba Cloud is a leading global cloud computing and infrastructure services provider originating from China, offering a wide range of scalable computing, storage, and data solutions.
- F. None of above. chosen
Provenance (2 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6529875688190952af476aa5be492 |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:47 p.m.