Triple
T8993155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OS/VS1 |
E214837
|
entity |
| Predicate | supportsSubsystem |
P13398
|
FINISHED |
| Object | IMS |
E206675
|
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: IMS | Statement: [OS/VS1, supportsSubsystem, IMS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IMS Context triple: [OS/VS1, supportsSubsystem, IMS]
-
A.
IMS
IMS (IP Multimedia Subsystem) is a standardized architectural framework for delivering IP-based multimedia services over mobile and fixed networks.
-
B.
IMS
IMS is a leading biomedical research institute focused on understanding metabolic diseases such as obesity and diabetes.
-
C.
IMS
IMS is the NATO International Military Staff, the body that provides strategic military advice and support to NATO’s decision-making structures.
-
D.
IMS
IMS is the IEEE MTT-S International Microwave Symposium, a leading annual conference and exhibition focused on microwave theory, techniques, and technologies.
-
E.
IMS
chosen
IMS is IBM's hierarchical database and transaction management system widely used on mainframe platforms for high-volume, mission-critical 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6876583081909d936dc3c3152587 |
completed | April 1, 2026, 12:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0cd2b948190947a26fe11ad81bf |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:04 p.m.