Triple
T14582244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BlackBerry Storm series |
E342220
|
entity |
| Predicate | hasIssueReported |
P90681
|
FINISHED |
| Object | mixed reviews of SurePress screen |
—
|
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: mixed reviews of SurePress screen | Statement: [BlackBerry Storm series, hasIssueReported, mixed reviews of SurePress screen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIssueReported Context triple: [BlackBerry Storm series, hasIssueReported, mixed reviews of SurePress screen]
-
A.
hasRecentIssue
Indicates that an entity is associated with an issue or problem that has occurred within a recent or specified time frame.
-
B.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
C.
hadIssue
chosen
Indicates that an entity experienced, encountered, or was affected by a particular problem, defect, or difficulty.
-
D.
hasNoIssue
Indicates that there are no problems, defects, or conflicts associated with the referenced entity or situation.
-
E.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb41e71748190a1deacc819dd26d3 |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.