Triple
T11472330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Discovery Turbo |
E271938
|
entity |
| Predicate | hasProgrammingTheme |
P99468
|
FINISHED |
| Object | speed |
—
|
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: speed | Statement: [Discovery Turbo, hasProgrammingTheme, speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProgrammingTheme Context triple: [Discovery Turbo, hasProgrammingTheme, speed]
-
A.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
B.
hasProgrammingDomain
Indicates that an entity is associated with or specializes in a particular programming domain or area of software development.
-
C.
hasProgrammingFrom
Indicates that something derives its programming, configuration, or behavioral instructions from a specified source.
-
D.
hasProgramme
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
-
E.
hasTechnologyTheme
Indicates that something is associated with, centers on, or prominently features technology as a primary theme or subject.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294b3f388190a587c358313f7260 |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d8279925e4819089210611c0d8e61a |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:35 p.m.