Triple
T5425808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picard iteration |
E121358
|
entity |
| Predicate | typicalSpace |
P51618
|
FINISHED |
| Object | space of continuous functions on a closed interval |
—
|
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: space of continuous functions on a closed interval | Statement: [Picard iteration, typicalSpace, space of continuous functions on a closed interval]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSpace Context triple: [Picard iteration, typicalSpace, space of continuous functions on a closed interval]
-
A.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
-
C.
typicalStateSpace
chosen
Indicates the usual or standard set of states in which an entity, system, or process is considered to operate.
-
D.
typicalChamber
Indicates that something is a standard or characteristic chamber associated with a given context or entity.
-
E.
openSpaceType
Indicates the type or category of an open space associated with an entity (e.g., park, plaza, courtyard).
- 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_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. |
Created at: March 20, 2026, 2:06 p.m.