Triple
T2652934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitney approximation theorem |
E53941
|
entity |
| Predicate | topologyUsed |
P33685
|
FINISHED |
| Object | compact-open topology |
—
|
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: compact-open topology | Statement: [Whitney approximation theorem, topologyUsed, compact-open topology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topologyUsed Context triple: [Whitney approximation theorem, topologyUsed, compact-open topology]
-
A.
usesTopology
chosen
Indicates that one entity employs, is based on, or operates according to a particular topology defined or provided by another entity.
-
B.
hasTopology
Indicates that one entity possesses, exhibits, or is characterized by a particular structural or spatial configuration defined by the other entity.
-
C.
typicalTopology
Indicates the usual or most common network or structural arrangement that characterizes how the related entities are organized or interconnected.
-
D.
topology
Indicates the structural or spatial arrangement and connectivity pattern among components within a system.
-
E.
topographyBasedOn
Indicates that the topographical characteristics of one entity are derived from, determined by, or modeled using the topography of another entity.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.