Triple
T4923643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whyte notation |
E110523
|
entity |
| Predicate | firstNumberRepresents |
P35107
|
FINISHED |
| Object | leading wheels |
—
|
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: leading wheels | Statement: [Whyte notation, firstNumberRepresents, leading wheels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstNumberRepresents Context triple: [Whyte notation, firstNumberRepresents, leading wheels]
-
A.
firstPartRepresents
Indicates that the initial segment or portion of something stands for, symbolizes, or denotes a larger whole or specific concept.
-
B.
isFirstNumberOneFor
Indicates that the first number in a given pair, sequence, or context is equal to one for the associated entity or situation.
-
C.
firstDigitEncoding
chosen
Indicates that one entity encodes or represents the first digit of another entity (such as a number, code, or identifier).
-
D.
secondLetterRepresents
Indicates that the second letter of one entity stands for, symbolizes, or denotes another entity or concept.
-
E.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
- 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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffd46748190843fed99f02fd8d5 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3695c8819094e7ad2f6d4ba1ac |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.