Triple
T11214938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dehn surgery |
E265411
|
entity |
| Predicate | typicalAmbientSpace |
P28977
|
FINISHED |
| Object | 3-sphere S^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: 3-sphere S^3 | Statement: [Dehn surgery, typicalAmbientSpace, 3-sphere S^3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAmbientSpace Context triple: [Dehn surgery, typicalAmbientSpace, 3-sphere S^3]
-
A.
ambientSpace
chosen
Indicates the surrounding or containing space within which an object, structure, or geometric entity is situated or defined.
-
B.
spaceType
Indicates the category or kind of physical or conceptual space associated with an entity.
-
C.
typicalChamber
Indicates that something is a standard or characteristic chamber associated with a given context or entity.
-
D.
typeOfBuildingSpace
Indicates the specific kind or category of building space that an entity represents or occupies.
-
E.
typicalSeat
Indicates the usual or standard seating position or location associated with an entity in a given 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8e8eef48190932a85784ce15c86 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d75cfbbb188190861efd5d94fe27da |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:30 p.m.