Graphical models as representations for IE consistently perform better relative to n-gram models on sparse words, but not necessarily polysemous words.
. | polysemous . | not-polysemous . | sparse . | not-sparse . |
|---|---|---|---|---|
| types | 222 | 210 | 266 | 166 |
| categs. | 12 | 4 | 13 | 3 |
| n-Gram-R | 0.07 | 0.17 | 0.06 | 0.25 |
| Lattice-Type-R | 0.09 | 0.15 | 0.1 | 0.19 |
| -n-Gram-R | +0.02 | −0.02 | +0.04 | −0.06 |
| HMM-Type-R | 0.14 | 0.26 | 0.15 | 0.32 |
| -n-Gram-R | +0.07 | +0.09 | +0.09 | +0.07 |
. | polysemous . | not-polysemous . | sparse . | not-sparse . |
|---|---|---|---|---|
| types | 222 | 210 | 266 | 166 |
| categs. | 12 | 4 | 13 | 3 |
| n-Gram-R | 0.07 | 0.17 | 0.06 | 0.25 |
| Lattice-Type-R | 0.09 | 0.15 | 0.1 | 0.19 |
| -n-Gram-R | +0.02 | −0.02 | +0.04 | −0.06 |
| HMM-Type-R | 0.14 | 0.26 | 0.15 | 0.32 |
| -n-Gram-R | +0.07 | +0.09 | +0.09 | +0.07 |