Neural Cross-Lingual Entity Linking
Authors: Avirup Sil, Gourab Kundu, Radu Florian, Wael Hamza
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The proposed system has strong empirical evidence yielding state-of-the-art results in English as well as cross-lingual: Spanish and Chinese TAC 2015 datasets. |
| Researcher Affiliation | Industry | Avirup Sil, Gourab Kundu, Radu Florian, Wael Hamza IBM Research AI 1101 Kitchawan Road Yorktown Heights, NY 10598 {avi, gkundu, raduf, whamza}@us.ibm.com |
| Pseudocode | No | The paper does not include any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | We evaluate our proposed method on the benchmark datasets for English: Co NLL 2003 and TAC 2010 and Cross Lingual: TAC 2015 Trilingual Entity Linking dataset. |
| Dataset Splits | Yes | We use standard train, validation and test splits if the datasets come with it, else we use the Co NLL validation data as dev. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used to run the experiments, such as GPU or CPU models. |
| Software Dependencies | No | The paper mentions various models and systems (e.g., word2vec, LSTMs, LIEL) but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | We run CNNs on the sentences and the Wikipedia embeddings with filter size of 300 and width 2. The non-linearity used is tanh. For both forward (left) and backward (right) LSTMs, we use mean pooling... For the NTNs, we use sigmoid as the non-linearity and an output size of 10 and use L2 regularization with a value of 0.01. ... For the main model, we again use sigmoid non-linearity and an output size of 1000 with a dropout rate of 0.4. ... For the MPBL node, the number of dimensions is 100. |