Triple
T19531729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamming code |
E488671
|
entity |
| Predicate | parityBitPositions |
P76800
|
FINISHED |
| Object | powers of two |
—
|
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: powers of two | Statement: [Hamming code, parityBitPositions, powers of two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parityBitPositions Context triple: [Hamming code, parityBitPositions, powers of two]
-
A.
parityBits
chosen
Indicates that there is an association between data and the parity bits used to detect or correct errors in that data.
-
B.
bitRepresentation
Indicates that one entity is the binary (bit-level) representation or encoding of another entity.
-
C.
bitOrder
Indicates the ordering or sequence of bits within a binary representation, such as which bit positions are considered first or most significant.
-
D.
hasParity
Indicates that two entities share the same parity property (e.g., both even or both odd) with respect to a specified attribute or value.
-
E.
hasParityPatterns
Indicates that there is a specific pattern or regularity in the parity (odd/even characteristics) associated with the related entities.
- 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.