Runs - Tasks 2017¶
BJUT_1¶
Results
| Participants
| Proceedings
| Input
| Summary
| Appendix
- Run ID: BJUT_1
- Participant: BJUT
- Track: Tasks
- Year: 2017
- Submission: 8/20/2017
- Task: understanding
- MD5:
93d7c6c0d77f0be578668c1fc87c1aa2
- Run description: It's my first run. I used Bing search api,Google search api,Bing suggestion api
BJUT_2¶
Results
| Participants
| Proceedings
| Input
| Summary
| Appendix
- Run ID: BJUT_2
- Participant: BJUT
- Track: Tasks
- Year: 2017
- Submission: 8/22/2017
- Task: understanding
- MD5:
218973ac5850211bc1ab34d839e8aeec
- Run description: it's my second run, I used bing suggestion search api and google suggestion search api.
SienaCLTeamRun1¶
Results
| Participants
| Proceedings
| Input
| Summary
| Appendix
- Run ID: SienaCLTeamRun1
- Participant: SienaCLTeam
- Track: Tasks
- Year: 2017
- Submission: 8/22/2017
- Task: understanding
- MD5:
7fffe9cef4e2c0582f3d5c52dbc05ae2
- Run description: This run augmented the original queries with the most common noun phrases from top Google results. It utilized the Stanford parser. It generated up to 20 new queries. The run was entirely automatic - no manual steps were needed.
SienaCLTeamRun2¶
Results
| Participants
| Proceedings
| Input
| Summary
| Appendix
- Run ID: SienaCLTeamRun2
- Participant: SienaCLTeam
- Track: Tasks
- Year: 2017
- Submission: 8/24/2017
- Task: understanding
- MD5:
0193463ea9af057f0f1e061dd0097ce2
- Run description: Utilized Wordnet synonyms and hypernyms for query generation. When few results augment with our Run1 results