Triple
T15889265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Böhm–Jacopini theorem |
E385272
|
entity |
| Predicate | typicalControlStructures |
P120951
|
FINISHED |
| Object | if-then-else |
—
|
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: if-then-else | Statement: [Böhm–Jacopini theorem, typicalControlStructures, if-then-else]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalControlStructures Context triple: [Böhm–Jacopini theorem, typicalControlStructures, if-then-else]
-
A.
controlStructure
Indicates a relationship where one entity governs, regulates, or directs the behavior, operation, or flow of another entity or process.
-
B.
structuralControlOn
Indicates that one entity exerts structural influence or constraint over another, affecting its form, configuration, or organization.
-
C.
typicalCircuit
Indicates that one entity is a standard or commonly occurring circuit configuration or pattern associated with another entity.
-
D.
controlsWith
Indicates that one entity exercises authority, direction, or regulatory power over another entity through specific means or mechanisms.
-
E.
programStructure
Indicates how components, modules, or elements are organized and related within a program or system.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:51 a.m.