Triple
T5890985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darwinsys Java Cookbook examples |
E130986
|
entity |
| Predicate | exampleType |
P67300
|
FINISHED |
| Object | code recipes |
—
|
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: code recipes | Statement: [Darwinsys Java Cookbook examples, exampleType, code recipes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleType Context triple: [Darwinsys Java Cookbook examples, exampleType, code recipes]
-
A.
exampleApplication
Indicates that something serves as a representative or illustrative instance of how an application is used or functions.
-
B.
seeType
Indicates that one entity observes, recognizes, or visually perceives another entity of a particular type or category.
-
C.
testType
Indicates the specific category or kind of test associated with an entity or event.
-
D.
showType
Indicates the category or format in which something is presented or displayed (e.g., type of show, presentation, or display mode).
-
E.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03fe07b7081909f8577ec3a9a1a8d |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0334bdc308190ad0d7199ab975588 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03fdf954c8190ae97a5c9ce40bdfa |
completed | March 22, 2026, 7:15 p.m. |
Created at: March 22, 2026, 3:58 p.m.