Triple
T4092237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebesgue spaces |
E87728
|
entity |
| Predicate | LpInclusion |
P1393
|
FINISHED |
| Object | L^q ⊆ L^p under suitable measure conditions when q > p |
—
|
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: L^q ⊆ L^p under suitable measure conditions when q > p | Statement: [Lebesgue spaces, LpInclusion, L^q ⊆ L^p under suitable measure conditions when q > p]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LpInclusion Context triple: [Lebesgue spaces, LpInclusion, L^q ⊆ L^p under suitable measure conditions when q > p]
-
A.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
B.
isUpperBoundFor
Indicates that one value is greater than or equal to every element in a given set or collection, serving as an upper limit for them.
-
C.
reasoningIncludes
Indicates that a reasoning process or argument explicitly incorporates or makes use of the referenced element as one of its components or steps.
-
D.
rangeIncludes
Indicates that the values or results associated with a property are expected to be of the specified type or types.
-
E.
LagrangianContains
Indicates that a given term, field, or interaction is included as part of the Lagrangian in a physical or mathematical model.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcae22a081908af65a960306b78c |
completed | March 9, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:40 p.m.