Title: Tracing application of lexicon rules · Issue #9 · bmeaut/python_nlp_2017_fall · GitHub
Open Graph Title: Tracing application of lexicon rules · Issue #9 · bmeaut/python_nlp_2017_fall
X Title: Tracing application of lexicon rules · Issue #9 · bmeaut/python_nlp_2017_fall
Description: Hello everyone, Is there a way through which I'd be able to trace which rules in my lexicons have been applied when a surface form is transduced into a deep representation? I mean apart from "instrumenting" my lexicon rules with dummy ta...
Open Graph Description: Hello everyone, Is there a way through which I'd be able to trace which rules in my lexicons have been applied when a surface form is transduced into a deep representation? I mean apart from "instr...
X Description: Hello everyone, Is there a way through which I'd be able to trace which rules in my lexicons have been applied when a surface form is transduced into a deep representation? I mean apart from &q...
Opengraph URL: https://github.com/bmeaut/python_nlp_2017_fall/issues/9
X: @github
Domain: patch-diff.githubusercontent.com
{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Tracing application of lexicon rules","articleBody":"Hello everyone,\r\n\r\nIs there a way through which I'd be able to trace which rules in my lexicons have been applied when a surface form is transduced into a deep representation? I mean apart from \"instrumenting\" my lexicon rules with dummy tag identifiers which tell me unambiguously which rule was applied? I have a minor problem: my grammar is correct in a sense that it finds the appropriate representation, but it finds it twice. And I can't seem to pinpoint the cause. It is related to the superlative form of adjectives. If the word contains the -bb postfix, then there are always two solutions, completely identical. Since I believe only one derivation is possible, I'm very interested which two derivations did apply_up find. I already printed the automaton with draw_net, but it is not evident to me how that automaton could recognize the word twice.","author":{"url":"https://github.com/dobijan","@type":"Person","name":"dobijan"},"datePublished":"2017-11-27T09:07:45.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":3},"url":"https://github.com/9/python_nlp_2017_fall/issues/9"}
| route-pattern | /_view_fragments/issues/show/:user_id/:repository/:id/issue_layout(.:format) |
| route-controller | voltron_issues_fragments |
| route-action | issue_layout |
| fetch-nonce | v2:79047e61-1e71-8b74-b842-ca1c68863ab4 |
| current-catalog-service-hash | 81bb79d38c15960b92d99bca9288a9108c7a47b18f2423d0f6438c5b7bcd2114 |
| request-id | A646:235E6A:C5ADF6:1004CEE:6991FDC9 |
| html-safe-nonce | c3a5b7fce7ebda306234565a160c3ce80193877bbcd56eeabac9221d72c86eb9 |
| visitor-payload | eyJyZWZlcnJlciI6IiIsInJlcXVlc3RfaWQiOiJBNjQ2OjIzNUU2QTpDNUFERjY6MTAwNENFRTo2OTkxRkRDOSIsInZpc2l0b3JfaWQiOiI2Njc0MDQxMDcxMzM5Njk5NjU3IiwicmVnaW9uX2VkZ2UiOiJpYWQiLCJyZWdpb25fcmVuZGVyIjoiaWFkIn0= |
| visitor-hmac | 550cb6e9775d6cdd9481c4cc56eecf7afcfc3a235899eb30d44f256b2d0618dd |
| hovercard-subject-tag | issue:276945100 |
| github-keyboard-shortcuts | repository,issues,copilot |
| google-site-verification | Apib7-x98H0j5cPqHWwSMm6dNU4GmODRoqxLiDzdx9I |
| octolytics-url | https://collector.github.com/github/collect |
| analytics-location | / |
| fb:app_id | 1401488693436528 |
| apple-itunes-app | app-id=1477376905, app-argument=https://github.com/_view_fragments/issues/show/bmeaut/python_nlp_2017_fall/9/issue_layout |
| twitter:image | https://opengraph.githubassets.com/bc5e1ae1af29600b7c760a8e21665b7f904e6b4275b6cd6ceaa2b8be2d22bee4/bmeaut/python_nlp_2017_fall/issues/9 |
| twitter:card | summary_large_image |
| og:image | https://opengraph.githubassets.com/bc5e1ae1af29600b7c760a8e21665b7f904e6b4275b6cd6ceaa2b8be2d22bee4/bmeaut/python_nlp_2017_fall/issues/9 |
| og:image:alt | Hello everyone, Is there a way through which I'd be able to trace which rules in my lexicons have been applied when a surface form is transduced into a deep representation? I mean apart from "instr... |
| og:image:width | 1200 |
| og:image:height | 600 |
| og:site_name | GitHub |
| og:type | object |
| og:author:username | dobijan |
| hostname | github.com |
| expected-hostname | github.com |
| None | 42c603b9d642c4a9065a51770f75e5e27132fef0e858607f5c9cb7e422831a7b |
| turbo-cache-control | no-preview |
| go-import | github.com/bmeaut/python_nlp_2017_fall git https://github.com/bmeaut/python_nlp_2017_fall.git |
| octolytics-dimension-user_id | 12133481 |
| octolytics-dimension-user_login | bmeaut |
| octolytics-dimension-repository_id | 102472656 |
| octolytics-dimension-repository_nwo | bmeaut/python_nlp_2017_fall |
| octolytics-dimension-repository_public | true |
| octolytics-dimension-repository_is_fork | false |
| octolytics-dimension-repository_network_root_id | 102472656 |
| octolytics-dimension-repository_network_root_nwo | bmeaut/python_nlp_2017_fall |
| turbo-body-classes | logged-out env-production page-responsive |
| disable-turbo | false |
| browser-stats-url | https://api.github.com/_private/browser/stats |
| browser-errors-url | https://api.github.com/_private/browser/errors |
| release | 848bc6032dcc93a9a7301dcc3f379a72ba13b96e |
| ui-target | canary-2 |
| theme-color | #1e2327 |
| color-scheme | light dark |
Links:
Viewport: width=device-width