Triple
T19531730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamming code |
E488671
|
entity |
| Predicate | syndromeDecoding |
P14388
|
FINISHED |
| Object | used |
—
|
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: used | Statement: [Hamming code, syndromeDecoding, used]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: syndromeDecoding Context triple: [Hamming code, syndromeDecoding, used]
-
A.
usesForwardErrorCorrection
Indicates that one entity applies forward error correction techniques to detect and correct errors in data transmitted to or received from another entity.
-
B.
coDecipherer
Indicates that two or more entities jointly participated in deciphering or decoding something together.
-
C.
parityBits
Indicates that there is an association between data and the parity bits used to detect or correct errors in that data.
-
D.
deciphers
Indicates the action of successfully interpreting or figuring out the meaning of something that is difficult to understand or encoded.
-
E.
decodingMethod
chosen
Indicates the technique or process used to convert encoded or encrypted data back into its original, interpretable form.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6363fd1f8819080805346efad2579 |
completed | April 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69e514c9c00481909b76bda67957e58b |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.