Triple
T2105618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 3414 |
E37187
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | USM |
E189499
|
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: USM | Statement: [RFC 3414, abbreviation, USM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USM Context triple: [RFC 3414, abbreviation, USM]
-
A.
USM
chosen
USM (User-based Security Model) is the SNMPv3 security framework that provides user-level authentication, privacy (encryption), and access control for Simple Network Management Protocol communications.
-
B.
USMIA
USMIA is the UN/LOCODE identifier for the port and transport hub of Miami in the United States.
-
C.
UME
UME is Spain’s specialized military emergency unit responsible for rapid response to natural disasters, major accidents, and other civil emergencies.
-
D.
UM
UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
-
E.
UM
UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbadcd4a081909d60b9b241950335 |
completed | March 7, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae306bee8881908c62306fb1f6aea1 |
completed | March 9, 2026, 2:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.