Triple
T16402861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smale horseshoe |
E398342
|
entity |
| Predicate | invariantSet |
P123287
|
FINISHED |
| Object | Cantor set |
—
|
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: Cantor set | Statement: [Smale horseshoe, invariantSet, Cantor set]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: invariantSet Context triple: [Smale horseshoe, invariantSet, Cantor set]
-
A.
invariantOf
Indicates that one element is an invariant (a property or quantity that remains unchanged) with respect to another element, system, or transformation.
-
B.
invariantUnder
Indicates that a property, structure, or quantity remains unchanged when a specified transformation or operation is applied.
-
C.
invariantType
Indicates that one entity has a type or classification that remains constant or unchanged under specified conditions or transformations.
-
D.
setsIn
Indicates that one entity places or positions another entity into or within a specified container, location, or context.
-
E.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
- F. None of above. chosen
Provenance (4 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d0652081908f42f78b156f3ae7 |
completed | April 18, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.