Triple
T23363216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UICC |
E593240
|
entity |
| Predicate | supportsApplication |
P15794
|
FINISHED |
| Object | SIM |
—
|
NE NERFINISHED |
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: SIM | Statement: [UICC, supportsApplication, SIM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SIM Context triple: [UICC, supportsApplication, SIM]
-
A.
SIM
chosen
SIM (Subscriber Identity Module) is a secure smart card or embedded chip used in mobile devices to store subscriber credentials and enable authentication and access to cellular networks.
-
B.
SIM
SIM is the National Rail station code assigned to Simonside Metro station in South Tyneside, England.
-
C.
SIM
SIM is the commonly used abbreviation for the Science and Industry Museum in Manchester, a major UK museum dedicated to the history and impact of science, technology, and industry.
-
D.
SIM
SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
-
E.
IMS
IMS is the NATO International Military Staff, the body that provides strategic military advice and support to NATO’s decision-making structures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aa0ed88190b0198cbfd1bcc59b |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 17, 2026, 5:30 p.m.