Triple
T10825953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | python-dev mailing list |
E255497
|
entity |
| Predicate | notFocusedOn |
P57963
|
FINISHED |
| Object | general beginner Python questions |
—
|
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: general beginner Python questions | Statement: [python-dev mailing list, notFocusedOn, general beginner Python questions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notFocusedOn Context triple: [python-dev mailing list, notFocusedOn, general beginner Python questions]
-
A.
lessFocusOn
Indicates that one entity directs reduced attention, emphasis, or priority toward another entity or activity compared to alternatives.
-
B.
notAbout
chosen
Indicates that a given entity, statement, or resource does not concern, reference, or pertain to another specified entity or topic.
-
C.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d1c24881909f56d56207cccbef |
completed | April 9, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:19 p.m.