Triple
T36640370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SL(2,7) |
E904566
|
entity |
| Predicate | hasSmallestFieldSize |
P64837
|
FINISHED |
| Object | 7 for nontrivial SL(2,q) with q>3 |
—
|
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: 7 for nontrivial SL(2,q) with q>3 | Statement: [SL(2,7), hasSmallestFieldSize, 7 for nontrivial SL(2,q) with q>3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSmallestFieldSize Context triple: [SL(2,7), hasSmallestFieldSize, 7 for nontrivial SL(2,q) with q>3]
-
A.
hasMinimumSize
Indicates that an entity meets or exceeds a specified minimum size threshold.
-
B.
isSmallestOf
chosen
Indicates that an entity has the minimum size or value within a specified set or group of entities.
-
C.
hasFieldLength
Indicates that an entity possesses a field whose length (such as number of characters or size) is specified or constrained.
-
D.
minimumSize
Indicates that there is a lower bound or smallest allowable value for the size of something in the relationship.
-
E.
hasSmallestTypicalElement
Indicates that, within a given collection or set, one element is designated as the smallest among those considered typical or representative for that collection.
- 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_69f76e6c63e48190b1d0c3a79a6c7406 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.