Triple
T14394789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DataGrip |
E356925
|
entity |
| Predicate | supportsLanguage |
P2177
|
FINISHED |
| Object | Vertica SQL dialect |
E991161
|
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: Vertica SQL dialect | Statement: [DataGrip, supportsLanguage, Vertica SQL dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vertica SQL dialect Context triple: [DataGrip, supportsLanguage, Vertica SQL dialect]
-
A.
Vertica
chosen
Vertica is a high-performance, column-oriented analytical database system designed for large-scale data warehousing and real-time analytics.
-
B.
Teradata
Teradata is an enterprise-grade relational database management system and data warehousing platform designed for large-scale analytics and business intelligence workloads.
-
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.
VoltDB
VoltDB is a high-performance, in-memory, distributed SQL database designed for real-time analytics and transaction processing at massive scale.
-
E.
BlazingSQL
BlazingSQL is an open-source SQL engine that enables GPU-accelerated data processing and analytics, often used within the NVIDIA RAPIDS ecosystem for high-performance query execution on large datasets.
- 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.