Triple
T8248395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hydra |
E192900
|
entity |
| Predicate | supportsProtocol |
P203
|
FINISHED |
| Object | MSSQL |
E7155
|
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: MSSQL | Statement: [Hydra, supportsProtocol, MSSQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MSSQL Context triple: [Hydra, supportsProtocol, MSSQL]
-
A.
SQL Server
chosen
SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
-
B.
MSIServer
MSIServer is the Windows service that manages installation, modification, and removal of software using the Windows Installer technology.
-
C.
SQL Server Management Studio
SQL Server Management Studio is a graphical administration and development environment used to configure, manage, and query Microsoft SQL Server databases.
-
D.
Sybase
Sybase is a pioneering enterprise software company best known for its relational database management systems and data management solutions, later acquired by SAP.
-
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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c6b3c48190a3ecebf449766124 |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd680b0f608190b69336228346b47d |
completed | April 1, 2026, 6:46 p.m. |
Created at: March 30, 2026, 5:48 p.m.