Triple
T24813626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Automator |
E620854
|
entity |
| Predicate | requiresProgrammingKnowledge |
P159691
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Automator, requiresProgrammingKnowledge, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresProgrammingKnowledge Context triple: [Automator, requiresProgrammingKnowledge, no]
-
A.
providedProgramming
Indicates that one entity supplied or made available programming (such as software, code, or a program) to another entity.
-
B.
requiresTraining
Indicates that one entity can only be properly or legitimately used, performed, or engaged with if the other entity has first received appropriate training.
-
C.
requiresPractice
Indicates that performing or mastering one entity depends on engaging in repeated practice or training involving another entity.
-
D.
prerequisiteKnowledge
Indicates that one piece of knowledge must be acquired or understood before another can be effectively learned or applied.
-
E.
programmingIncludes
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5f7a205688190b8f36bff5013247c |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 18, 2026, 4:59 a.m.