implement a model that predicts opinion polarities (positive, negative or neutral) for given aspect terms in sentences. The model takes as input 3 elements: a sentence, a term occurring in the sentence, and its aspect category. For each input triple, it produces a polarity label: positive, negative or neutral.
active 2024-03-06 → 2024-03-12 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 7 days from 2024-03-06 to 2024-03-12. Pushes: 3 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| theveneth | 2 | 2 | 0 | 0 |
| markpiquant | 1 | 1 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.