Triple
T1368273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magento |
E30050
|
entity |
| Predicate | uses |
P98
|
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: [Magento, uses, MySQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MySQL Context triple: [Magento, uses, 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 HeatWave
MySQL HeatWave is a fully managed, in-memory query acceleration and analytics engine integrated with MySQL to deliver high-performance OLTP and OLAP processing on the same database service.
-
D.
DB
DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
-
E.
SQL
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d497f88190993d16a208ced43d |
completed | March 1, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acce7ae56c8190970bacb061a71798 |
completed | March 8, 2026, 1:18 a.m. |
Created at: March 1, 2026, 7:57 p.m.