1. Learning Adjective Meanings with a Tensor-Based Skip- Gram Model Review by – Masare Akshay Sunil Jean Millard & Stephan Clark University of Cambridge

2. Introduction

3. Similarity Measure

4. Training of Nouns Skip – Gram model with negative sampling Each noun is assigned two vectors: content vector(n) and context vector(n’) For each occurrence content vector is updated to maximize the objective function given below via back-propagation

5. Training of Adjectives Each adjective is assigned a matrix All adjective-noun pairs are extracted The matrix for any adjective is updated to maximize the function below via back propagation

6. Evaluation  Dataset Used: English Wikipedia dump with Clark and Curran parser  200 million nouns and 30 million adjectives  For every context word, 5 negative words are sampled  Noun vector – 100 dimensional, Adjective matrix – 100x100 dimensional

7. Word Similarity  Run on MEN test collection of POS-tagged word pairs  643 noun – noun pairs  96 adjective – adjective pairs  The results are calculated by using Spearman rank correlation on noun or adjective similarity. ModelCorrelation SkipGram-3000.776 TBSG-1000.769 ModelCorrelation TBSG-100 X 1000.645 SkipGram-3000.638 Results for Noun Results for Adjective

8. Phrase Similarity  Run on Mitchell and Lapata adjective- noun similarity dataset containing large pairs of adjective – noun phrases.  Spearman Rank correlation for cosine similarity of vectors in various models  Also compared to Human similarity judgement. ModelCorrelation TBSG-1000.50 SkipGram-300 (add)0.48 SkipGram-300 (N only)0.43 TBSG-100 (N only)0.42 REG-6000.37 Humans0.52 Results for Adjective – Noun pairs

9. Semantic Anomaly  Used to distinguish between acceptable and anomalous adjective – noun phrases ModelCosineDensity TBSG-1005.165.72 ADD-3000.312.63 MUL-300-0.562.68 REG-3000.483.12 Eg. Cultural Acne: Deviant phrase Eg. Ethical Statue: Unobserved acceptable Cosine similarity is the cosine between the adjective – noun vector and the noun vector. Density is the average cosine distance between the adjective – noun vector and its 10 nearest neighboours

10. Thank you