Triple
T5425412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schauder fixed-point theorem |
E121350
|
entity |
| Predicate | typeOfCompactness |
P63669
|
FINISHED |
| Object | image of bounded sets is relatively compact |
—
|
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: image of bounded sets is relatively compact | Statement: [Schauder fixed-point theorem, typeOfCompactness, image of bounded sets is relatively compact]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCompactness Context triple: [Schauder fixed-point theorem, typeOfCompactness, image of bounded sets is relatively compact]
-
A.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
B.
isCompact
Indicates that an object or space has a small, efficiently arranged size or volume relative to its function or contents.
-
C.
formationType
Indicates the specific structural or organizational configuration in which something is arranged, created, or formed.
-
D.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
-
E.
representationType
Indicates the specific form or mode in which something is represented or expressed (e.g., as a symbol, image, model, or description).
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8911a7348190ad9378a248190f07 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd846b8bdc81909dcdc2a3084226f2 |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8910de688190aa0cd80627849a60 |
completed | March 20, 2026, 5:51 p.m. |
Created at: March 20, 2026, 2:06 p.m.