Triple
T3167448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TOC |
E66245
|
entity |
| Predicate | isSimplifiedVersionOf |
P15288
|
FINISHED |
| Object | OSCAR protocol |
E66244
|
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: OSCAR protocol | Statement: [TOC, isSimplifiedVersionOf, OSCAR protocol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OSCAR protocol Context triple: [TOC, isSimplifiedVersionOf, OSCAR protocol]
-
A.
OSCAR
chosen
OSCAR is the proprietary messaging protocol developed by AOL to power its real-time chat and presence services across products like AIM and ICQ.
-
B.
OSCT
OSCT is the acronym for the UK government’s Office for Security and Counter-Terrorism, which leads national strategy and policy on counter-terrorism and security.
-
C.
Diffie–Hellman key exchange
Diffie–Hellman key exchange is a foundational cryptographic protocol that enables two parties to securely establish a shared secret over an insecure communication channel.
-
D.
OSPP
OSPP is the abbreviated name for the Office of Strategy, Policy, and Plans, a governmental body focused on developing and coordinating strategic policy initiatives.
-
E.
Mopria
Mopria is a universal mobile printing standard that enables seamless, driverless printing from devices like smartphones, tablets, and Chromebooks to compatible printers.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6457acc8190b2b9acbd1cfcdb91 |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235e108cc81909d5733bd00cb0bee |
completed | March 12, 2026, 3:41 a.m. |
Created at: March 8, 2026, 3:06 p.m.