```r
word_cors %>%
  filter(item1 == "pounds")
```

```
## # A tibble: 393 x 3
##    item1  item2       correlation
##    <chr>  <chr>             <dbl>
##  1 pounds thousand         0.769 
##  2 pounds ten              0.328 
##  3 pounds wickham's        0.204 
##  4 pounds settled          0.169 
##  5 pounds children         0.146 
##  6 pounds fortune          0.121 
##  7 pounds ready            0.106 
##  8 pounds particulars      0.106 
##  9 pounds town             0.101 
## 10 pounds believed         0.0959
## # ... with 383 more rows
```