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

```
## # A tibble: 393 x 3
##    item1  item2     correlation
##    <chr>  <chr>           <dbl>
##  1 pounds thousand       0.701 
##  2 pounds ten            0.231 
##  3 pounds fortune        0.164 
##  4 pounds settled        0.149 
##  5 pounds wickham's      0.142 
##  6 pounds children       0.129 
##  7 pounds mother's       0.119 
##  8 pounds believed       0.0932
##  9 pounds estate         0.0890
## 10 pounds ready          0.0860
## # … with 383 more rows
```