Triple
T9898106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ADO.NET |
E182224
|
entity |
| Predicate | supportsDataSource |
P24486
|
FINISHED |
| Object | MySQL |
E17668
|
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: MySQL | Statement: [ADO.NET, supportsDataSource, MySQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MySQL Context triple: [ADO.NET, supportsDataSource, MySQL]
-
A.
MySQL
chosen
MySQL is a widely used open-source relational database management system known for its reliability, performance, and role in powering many web applications and services.
-
B.
MariaDB
MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
-
C.
MySQL AB
MySQL AB was the Swedish company that developed and commercially supported the popular open-source MySQL relational database management system.
-
D.
Percona XtraDB
Percona XtraDB is an enhanced, high-performance fork of the InnoDB storage engine used in MySQL and MariaDB, optimized for improved scalability, reliability, and performance.
-
E.
Percona Server for MySQL
Percona Server for MySQL is an enhanced, open-source drop-in replacement for MySQL designed for improved performance, scalability, and reliability in demanding database environments.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4ac27d88190b8255f7e616f95c9 |
completed | April 2, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb17ed548190a2510a667dd988ca |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:40 p.m.