Triple
T14394787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DataGrip |
E356925
|
entity |
| Predicate | supportsLanguage |
P2177
|
FINISHED |
| Object | Amazon Redshift SQL dialect |
E17671
|
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 Redshift SQL dialect | Statement: [DataGrip, supportsLanguage, Amazon Redshift SQL dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon Redshift SQL dialect Context triple: [DataGrip, supportsLanguage, Amazon Redshift SQL dialect]
-
A.
Amazon Redshift
chosen
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
-
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.
Greenplum
Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
-
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.
PostgreSQL
PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de902d114881908a8f3c01b3c6d309 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551b006c8190b84449f2e2b59b62 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:16 a.m.