Triple
T20638661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 200GBASE-R PHYs |
E507157
|
entity |
| Predicate | supportsForwardErrorCorrection |
P22596
|
FINISHED |
| Object | yes |
—
|
LITERAL 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: yes | Statement: [200GBASE-R PHYs, supportsForwardErrorCorrection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsForwardErrorCorrection Context triple: [200GBASE-R PHYs, supportsForwardErrorCorrection, yes]
-
A.
usesForwardErrorCorrection
chosen
Indicates that one entity applies forward error correction techniques to detect and correct errors in data transmitted to or received from another entity.
-
B.
errorDetectionCapability
Indicates the ability of an entity to detect the presence of errors in data, processes, or operations.
-
C.
includesCorrectionsFor
Indicates that one item contains modifications, fixes, or amendments that address errors or issues present in another item.
-
D.
supportsHEVCEncode
Indicates that one entity provides the capability for another entity to perform HEVC (High Efficiency Video Coding) encoding.
-
E.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
- F. None of above.
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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad1163008190aa9df36750a952d2 |
completed | April 20, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69e5a0155bd48190b3c769a12cc2c83d |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 16, 2026, 11:42 a.m.