Triple
T10992134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fourier inversion theorem |
E259775
|
entity |
| Predicate | isFormulatedUsing |
P96516
|
FINISHED |
| Object | Lebesgue integration |
—
|
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: Lebesgue integration | Statement: [Fourier inversion theorem, isFormulatedUsing, Lebesgue integration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFormulatedUsing Context triple: [Fourier inversion theorem, isFormulatedUsing, Lebesgue integration]
-
A.
hasFormulation
Indicates that one entity is expressed, prepared, or configured in a particular form or composition defined by another entity.
-
B.
formulatedIn
Indicates that something was created, developed, or expressed within a particular context, place, or framework.
-
C.
isFormedFor
Indicates that something is created, established, or brought into existence for a particular purpose, function, or beneficiary.
-
D.
coFormulated
Indicates that two or more entities were jointly formulated, designed, or created together as part of the same process or product.
-
E.
hasFormulationType
Indicates the specific way something is physically prepared or presented, such as its dosage form, composition, or delivery format.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d1e918819090c71f5a077fa15a |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.