Open alexanderpanchenko opened 6 years ago
All predictions can be found here: https://www.dropbox.com/sh/gk1yqyi15a6v151/AAAPgxWR6FpJb-WCikXuGk4fa?dl=0
col0 | col1 | prediction | prediction_score | #paths |
---|---|---|---|---|
economics | environment | 1 | 0.9995301961898804 | 145 |
monkey | environment | 1 | 0.9991114735603333 | 1 |
balance | environment | 1 | 0.9988333582878113 | 55 |
lynx | environment | 1 | 0.9988332390785217 | 1 |
saltwater | environment | 1 | 0.9982742071151733 | 5 |
biotope | environment | 1 | 0.9978505373001099 | 1 |
plain | environment | 1 | 0.9972966313362122 | 22 |
estuary | environment | 1 | 0.996849000453949 | 18 |
shelf | environment | 1 | 0.9958900809288025 | 18 |
desert | environment | 1 | 0.9956746697425842 | 78 |
col0 | col1 | prediction | prediction_score | #paths |
---|---|---|---|---|
caramel | food | 1 | 0.8053730130195618 | 6 |
castella | food | 1 | 0.7408849596977234 | 1 |
pine | food | 1 | 0.7227337956428528 | 22 |
twist | food | 1 | 0.6970964670181274 | 12 |
sorbet | food | 1 | 0.6548916697502136 | 1 |
dew | food | 1 | 0.6468852758407593 | 6 |
cone | food | 1 | 0.645354688167572 | 5 |
juice | food | 1 | 0.6200062036514282 | 39 |
roe | food | 1 | 0.6140910387039185 | 7 |
harissa | food | 1 | 0.599799394607544 | 2 |
col0 | col1 | prediction | prediction_score | #paths |
---|---|---|---|---|
tribology | science | 0 | 0.2781708538532257 | 13 |
thermodynamics | science | 0 | 0.13678085803985596 | 38 |
sociolinguistics | science | 0 | 0.1182653158903122 | 1 |
syntax | science | 0 | 0.11715514212846756 | 18 |
econometrics | science | 0 | 0.0980641171336174 | 20 |
glaciology | science | 0 | 0.09769338369369507 | 16 |
isles | science | 0 | 0.09598596394062042 | 2 |
construction | science | 0 | 0.07844474166631699 | 310 |
bacteriology | science | 0 | 0.07381927967071533 | 27 |
pharmaceutics | science | 0 | 0.07086465507745743 | 2 |
And now path based
col0 | col1 | prediction | prediction_score | #paths |
---|---|---|---|---|
mechanical | environment | 1 | 0.999927282333374 | 2 |
wastage | environment | 1 | 0.9964731335639954 | 2 |
adaptation | environment | 1 | 0.9934678673744202 | 145 |
sensitive | environment | 1 | 0.9870176911354065 | 1 |
decontamination | environment | 1 | 0.9815698862075806 | 4 |
ships | environment | 1 | 0.9174445271492004 | 31 |
rodent | environment | 1 | 0.9081927537918091 | 5 |
desertification | environment | 1 | 0.8772224187850952 | 9 |
motor | environment | 1 | 0.813579797744751 | 9 |
volcanic | environment | 1 | 0.7295820116996765 | 1 |
col0 | col1 | prediction | prediction_score | #paths |
---|---|---|---|---|
kek | food | 1 | 1.0 | 2 |
lolly | food | 1 | 0.9998959302902222 | 2 |
teacake | food | 1 | 0.9993802309036255 | 2 |
nintendo | food | 1 | 0.9991999268531799 | 1 |
jeon | food | 1 | 0.9988155364990234 | 3 |
harissa | food | 1 | 0.9953378438949585 | 2 |
pho | food | 1 | 0.9928723573684692 | 2 |
platters | food | 1 | 0.9904733300209045 | 8 |
pepe | food | 1 | 0.9771053791046143 | 1 |
sancocho | food | 1 | 0.9601033329963684 | 4 |
col0 | col1 | prediction | prediction_score | #paths |
---|---|---|---|---|
biometry | science | 1 | 0.9999997615814209 | 3 |
interstellar | science | 1 | 0.9998096823692322 | 9 |
organization | science | 1 | 0.9997231364250183 | 585 |
organizations | science | 1 | 0.9996223449707031 | 159 |
film | science | 1 | 0.9995477795600891 | 670 |
neuroengineering | science | 1 | 0.9983460903167725 | 2 |
place | science | 1 | 0.99818354845047 | 429 |
esthetics | science | 1 | 0.9981158971786499 | 3 |
glaciology | science | 1 | 0.9965704679489136 | 16 |
pharmaceutics | science | 1 | 0.9963035583496094 | 2 |
important to confirm the unability of HypeNet to be used in taxonomy induction
Make the prediction (in the similar fashion as #2 ) but for all domain of the taxonomy induction challenge. The candidates are from the vocabulary of the domain-specific words (e.g. food, science, etc. ~500–1000 words).