Triple
T20726368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 400 Gigabit Ethernet |
E509444
|
entity |
| Predicate | usesEncoding |
P7661
|
FINISHED |
| Object | NRZ |
—
|
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: NRZ | Statement: [400 Gigabit Ethernet, usesEncoding, NRZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NRZ Context triple: [400 Gigabit Ethernet, usesEncoding, NRZ]
-
A.
NRZ
NRZ is the state-owned railway company responsible for operating and managing Zimbabwe’s national rail transport network.
-
B.
NRZI
NRZI (Non-Return-to-Zero Inverted) is a digital line coding scheme that represents binary data by inverting the signal level on a '1' and leaving it unchanged on a '0', commonly used in various networking and storage technologies.
-
C.
NRZ-L
chosen
NRZ-L (Non-Return-to-Zero-Level) is a digital line coding scheme in which binary data is represented by two distinct voltage levels that remain constant throughout each bit interval.
-
D.
NR
NR is the two-letter ISO 3166-1 alpha-2 country code assigned to the Republic of Nauru.
-
E.
NR
NR is the U.S. Navy’s Office of Naval Reactors, the organization responsible for the design, operation, and safety of naval nuclear propulsion systems.
- 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1e8b020819091d5788b90215ead |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:29 p.m.