Triple
T20657933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IEEE 802.3by |
E507675
|
entity |
| Predicate | definesForwardErrorCorrection |
P22596
|
FINISHED |
| Object | optional FEC mechanisms |
—
|
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: optional FEC mechanisms | Statement: [IEEE 802.3by, definesForwardErrorCorrection, optional FEC mechanisms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesForwardErrorCorrection Context triple: [IEEE 802.3by, definesForwardErrorCorrection, optional FEC mechanisms]
-
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.
parityBits
Indicates that there is an association between data and the parity bits used to detect or correct errors in that data.
-
C.
includesCorrectionsFor
Indicates that one item contains modifications, fixes, or amendments that address errors or issues present in another item.
-
D.
errorDetectionMethod
Indicates the method or technique used to detect errors in a process, system, or data.
-
E.
errorDetectionCapability
Indicates the ability of an entity to detect the presence of errors in data, processes, or operations.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2eefd5c8190a71d4be690a6ae0e |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.