Triple
T10167673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How to Report Bugs Effectively |
E235247
|
entity |
| Predicate | recommendsIncluding |
P58814
|
FINISHED |
| Object | software version |
—
|
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: software version | Statement: [How to Report Bugs Effectively, recommendsIncluding, software version]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendsIncluding Context triple: [How to Report Bugs Effectively, recommendsIncluding, software version]
-
A.
recommendedIn
chosen
Indicates that one entity is suggested or endorsed within the context, content, or scope of another entity (such as a document, list, or recommendation source).
-
B.
commendedFor
Indicates that one entity has expressed praise or approval toward another entity specifically because of a particular action, quality, or achievement.
-
C.
recommendation
Indicates that one entity suggests, endorses, or advises another entity as suitable or beneficial for a particular purpose or context.
-
D.
implementsRecommendationOf
Indicates that one entity carries out or puts into practice a recommendation that was proposed or issued by another entity.
-
E.
canRecommend
Indicates that one entity is able or authorized to suggest or endorse another entity as suitable or preferable.
- F. None of above.
Provenance (3 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6f64a48190883aefce58a65ca6 |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.