Triple
T4260480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NRZI |
E96090
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Non-Return-to-Zero Invert-on-ones |
E96090
|
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: Non-Return-to-Zero Invert-on-ones | Statement: [NRZI, alsoKnownAs, Non-Return-to-Zero Invert-on-ones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Non-Return-to-Zero Invert-on-ones Context triple: [NRZI, alsoKnownAs, Non-Return-to-Zero Invert-on-ones]
-
A.
NRZI
chosen
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.
-
B.
Manchester encoding
Manchester encoding is a digital line code that represents each data bit with a transition in the middle of the bit period, providing both clock and data synchronization on the same signal.
-
C.
Scott encoding
Scott encoding is a method in lambda calculus for representing algebraic data types and their pattern matching behavior using higher-order functions.
-
D.
Golomb
Golomb is a station on the Carmelit underground funicular system in Haifa, Israel.
-
E.
LDPC
LDPC (Low-Density Parity-Check) is a powerful class of linear error-correcting codes known for near-Shannon-limit performance and widespread use in modern high-throughput communication systems.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f8103b48190934a810faafa6cb7 |
completed | March 12, 2026, 11:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b78c93c48190a4274f0de3fc2d25 |
completed | March 14, 2026, 7:31 p.m. |
Created at: March 12, 2026, 11:06 p.m.