Triple
T6908919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zariski topology |
E159881
|
entity |
| Predicate | compactnessType |
P63669
|
FINISHED |
| Object | quasi-compact but rarely compact Hausdorff |
—
|
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: quasi-compact but rarely compact Hausdorff | Statement: [Zariski topology, compactnessType, quasi-compact but rarely compact Hausdorff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compactnessType Context triple: [Zariski topology, compactnessType, quasi-compact but rarely compact Hausdorff]
-
A.
typeOfCompactness
chosen
Indicates the specific kind or category of compactness that characterizes an entity or structure.
-
B.
isCompact
Indicates that an object or space has a small, efficiently arranged size or volume relative to its function or contents.
-
C.
isNoncompact
Indicates that the object (such as a space or set) lacks compactness, meaning it does not satisfy the property that every open cover has a finite subcover.
-
D.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
-
E.
expansionType
Indicates the specific manner or category by which something grows, extends, or increases in scope or size.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9be98748190b5cb698e66e3aa42 |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.