Task: Language Identification
Input (Spanish, English): This paper aims to mine explicit rules from KB embedding space, and casts it into a sparse reconstruction problem. Experiments demonstrate its ability of extracting reasonable rules on a few link prediction datasets.  The solution part sounds plausible. However, it confuses me that why we need to mine rules from learned KB embeddings.   - It is still unclear what information these KB embeddings encode and it looks strange that we aim to learn rules including negation / disjunction from them.  - If the goal is to extract useful rules (for other applications), it is necessary to compare it to “graph random walk” (
Output (English): en