A Pattern-Based Approach to Recognizing Time Expressions
Authors: Wentao Ding, Guanji Gao, Linfeng Shi, Yuzhong Qu6335-6342
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show that PTime achieves a very competitive performance as compared with existing state-of-the-art approaches. |
| Researcher Affiliation | Academia | Wentao Ding, Guanji Gao, Linfeng Shi, Yuzhong Qu National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China {wtding, gjgao, lfshi}@smail.nju.edu.cn, yzqu@nju.edu.cn |
| Pseudocode | Yes | Algorithm 1: Algorithm for Pattern Selection; Algorithm 2: Greedy Select |
| Open Source Code | No | The detailed results including lists of selected patterns can be found at http://ws.nju.edu.cn/ptime. There is no explicit statement about releasing the source code for the methodology described in this paper. |
| Open Datasets | Yes | We evaluate our approach on the Temp Eval-3 (Uz Zaman et al. 2013), the Wiki Wars (Mazur and Dale 2010) and the Tweets (Zhong, Sun, and Cambria 2017). For the Temp Eval-3, we use the training and test sets splits following previous studies (Bethard 2013) i.e. use the Time Bank (Pustejovsky et al. 2003) corpus as the training set and the platinum-annotated corpus as the test set. |
| Dataset Splits | Yes | For development, we perform a 10-fold cross-validation on each training dataset. |
| Hardware Specification | Yes | running on a personal workstation with an Intel E3-1226 CPU of 3.30GHz. |
| Software Dependencies | No | The paper states the implementation is "written by Java and Scala" but does not provide specific version numbers for these languages or any libraries/frameworks used. |
| Experiment Setup | Yes | Parameter Settings We grid searched the value of ρ with a step of 0.01 for maximizing the strict match F1 score on each dataset. The values of ρ are set to 0.87, 0.94, 0.94 for Temp Eval-3, Wiki Wars and Tweets respectively. |