Triple
T1636192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Db2 |
E35363
|
entity |
| Predicate | hasEdition |
P35
|
FINISHED |
| Object | Db2 Big SQL |
E35363
|
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: Db2 Big SQL | Statement: [IBM Db2, hasEdition, Db2 Big SQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Db2 Big SQL Context triple: [IBM Db2, hasEdition, Db2 Big SQL]
-
A.
IBM DB2
chosen
IBM DB2 is a family of enterprise-grade relational database management systems developed by IBM, widely used for high-performance, scalable data storage and transaction processing across mainframe, distributed, and cloud environments.
-
B.
PostgreSQL
PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
-
C.
Amazon Redshift
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.
-
D.
MariaDB
MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
-
E.
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a17e8e08190afb78a953ab920ec |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58dbd0608190be207ab2bcdc9eef |
completed | March 8, 2026, 11:09 a.m. |
Created at: March 4, 2026, 7:28 p.m.