Build BOW model for Semantic Domain Identification

[janetzki]

Goal

We want to build a GNN-based edge prediction BOW model for SDI. We hypothesize that it has a higher performance than the simple baseline model.
Motivation: SDI with F1 > 0.30 for 1 tpi/meu

Tasks

• Acquire refined mappings from verses to semantic domains Acquire MARBLE Data #1
• use refined mappings from words in verses to SDs to assign SDs to words in verses from LRL
  • simply assign SDs in eng to each aligned word in LRL
  • if many false positive mappings (i.e., low precision): refine assignments with generated SD dicts for LRL (set intersection)
• collect BOW for every word with assigned SD (2 words before and after word in the middle)
• aggregate BOWs by SD
• perform SDI by extracting BOW for every candidate word in input sentence and compute cosine dist to aggregated BOW
• try out baseline: look up each word in a dictionary
• consider usefulness of WSD (word sense disambiguation) with pywsd or different tool: Eng verse → WordNet → SD (see Jonathan’s 2nd mail)