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PBOH[1] is a pure entity disambiguation approach (D2KB) based on light statistics from the English Wikipedia corpus. The authors develop a probabilistic graphical model using pairwise Markov Random Fields to address the problem of Entity Disambiguation. They show that pairwise co-occurrence statistics of words and entities are enough to obtain comparable or better performance than heavy feature engineered systems. They employ loopy belief propagation to perform inference at test time. PBOH can only be used for the D2KB task.
The text was updated successfully, but these errors were encountered:
Please implement PBOH by @octavian-ganea
https://github.com/dalab/pboh-entity-linking
PBOH[1] is a pure entity disambiguation approach (D2KB) based on light statistics from the English Wikipedia corpus. The authors develop a probabilistic graphical model using pairwise Markov Random Fields to address the problem of Entity Disambiguation. They show that pairwise co-occurrence statistics of words and entities are enough to obtain comparable or better performance than heavy feature engineered systems. They employ loopy belief propagation to perform inference at test time. PBOH can only be used for the D2KB task.
The text was updated successfully, but these errors were encountered: