Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
Authors: Matt Gardner, Jayant Krishnamurthy
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our open-vocabulary semantic parser on a fill-in-the-blank natural language query task. By giving open vocabulary semantic parsers direct access to KB information, we improve mean average precision on this task by over 120%. |
| Researcher Affiliation | Industry | Matt Gardner, Jayant Krishnamurthy Allen Institute for Artificial Intelligence Seattle, Washington, USA {mattg,jayantk}@allenai.org |
| Pseudocode | No | The paper describes the model components and equations but does not present structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | All of the data and code used in these experiments is available at http://github.com/allenai/open vocab semparse. |
| Open Datasets | Yes | We thus use the dataset introduced by Krishnamurthy and Mitchell (2015), which consists of the ClueWeb09 web corpus3 along with Google s FACC entity linking of that corpus to Freebase (Gabrilovich, Ringgaard, and Subramanya 2013). |
| Dataset Splits | Yes | We also used the test set created by Krishnamurthy and Mitchell, which contains 220 queries generated in the same fashion as the training data from a separate section of Clue Web. However, as they did not release a development set with their data, we used this set as a development set. For a final evaluation, we generated another, similar test set from a different held out section of Clue Web, in the same fashion as done by Krishnamurthy and Mitchell. This final test set contains 307 queries. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU, GPU models, memory, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | The paper mentions tools like a "CCG parser" and uses "Freebase", but it does not specify version numbers for any software dependencies or libraries used in their implementation. |
| Experiment Setup | Yes | In each of these models, we used vectors of size 300 for all embeddings. |