Triple
T264948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Internet Explorer |
E5702
|
entity |
| Predicate | operatingSystem |
P1593
|
FINISHED |
| Object | Windows Server |
E5904
|
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: Windows Server | Statement: [Internet Explorer, operatingSystem, Windows Server]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Windows Server Context triple: [Internet Explorer, operatingSystem, Windows Server]
-
A.
Windows
chosen
Windows is a widely used family of graphical operating systems developed by Microsoft for personal computers, servers, and other devices.
-
B.
Microsoft
Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
-
C.
Linux
Linux is a widely used open-source Unix-like operating system kernel that powers servers, desktops, mobile devices, and embedded systems around the world.
-
D.
Microsoft Edge
Microsoft Edge is a web browser developed by Microsoft that serves as the default browser for Windows and supports modern web standards and technologies.
-
E.
SQL Server
SQL Server is Microsoft's enterprise-grade relational database management system used for storing, managing, and analyzing data in a wide range of applications.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8f9bbc8190a13841e4de093a66 |
completed | Feb. 28, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a389ae45648190966804664bf4f861 |
completed | March 1, 2026, 12:34 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.