Convention for creating good data set for RASA NER_CRF












0















I am trying to create a dataset for training RASA ner_crf for one type of entity. Please let me know the minimum number of sentences/variation_in_sentence_formation for good result. When I have one type of each of the possible sentence NER_CRF is not giving good result.










share|improve this question



























    0















    I am trying to create a dataset for training RASA ner_crf for one type of entity. Please let me know the minimum number of sentences/variation_in_sentence_formation for good result. When I have one type of each of the possible sentence NER_CRF is not giving good result.










    share|improve this question

























      0












      0








      0








      I am trying to create a dataset for training RASA ner_crf for one type of entity. Please let me know the minimum number of sentences/variation_in_sentence_formation for good result. When I have one type of each of the possible sentence NER_CRF is not giving good result.










      share|improve this question














      I am trying to create a dataset for training RASA ner_crf for one type of entity. Please let me know the minimum number of sentences/variation_in_sentence_formation for good result. When I have one type of each of the possible sentence NER_CRF is not giving good result.







      rasa-nlu crf ner






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 23 '18 at 13:58









      Surabhi MundraSurabhi Mundra

      1468




      1468
























          1 Answer
          1






          active

          oldest

          votes


















          2














          Rasa entity extraction depends heavily on the pipeline you have defined. Also depends on language model and tokenizers. So make sure you use good tokenizer. If it is normal English utterances try using tokenizer_ spacy before ner_crf. Also try with ner_spacy



          As per my experience, 5 to 10 variations of utterances for each case gave a decent result to start with






          share|improve this answer























            Your Answer






            StackExchange.ifUsing("editor", function () {
            StackExchange.using("externalEditor", function () {
            StackExchange.using("snippets", function () {
            StackExchange.snippets.init();
            });
            });
            }, "code-snippets");

            StackExchange.ready(function() {
            var channelOptions = {
            tags: "".split(" "),
            id: "1"
            };
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function() {
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled) {
            StackExchange.using("snippets", function() {
            createEditor();
            });
            }
            else {
            createEditor();
            }
            });

            function createEditor() {
            StackExchange.prepareEditor({
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: true,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: 10,
            bindNavPrevention: true,
            postfix: "",
            imageUploader: {
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            },
            onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            });


            }
            });














            draft saved

            draft discarded


















            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53448063%2fconvention-for-creating-good-data-set-for-rasa-ner-crf%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown

























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            2














            Rasa entity extraction depends heavily on the pipeline you have defined. Also depends on language model and tokenizers. So make sure you use good tokenizer. If it is normal English utterances try using tokenizer_ spacy before ner_crf. Also try with ner_spacy



            As per my experience, 5 to 10 variations of utterances for each case gave a decent result to start with






            share|improve this answer




























              2














              Rasa entity extraction depends heavily on the pipeline you have defined. Also depends on language model and tokenizers. So make sure you use good tokenizer. If it is normal English utterances try using tokenizer_ spacy before ner_crf. Also try with ner_spacy



              As per my experience, 5 to 10 variations of utterances for each case gave a decent result to start with






              share|improve this answer


























                2












                2








                2







                Rasa entity extraction depends heavily on the pipeline you have defined. Also depends on language model and tokenizers. So make sure you use good tokenizer. If it is normal English utterances try using tokenizer_ spacy before ner_crf. Also try with ner_spacy



                As per my experience, 5 to 10 variations of utterances for each case gave a decent result to start with






                share|improve this answer













                Rasa entity extraction depends heavily on the pipeline you have defined. Also depends on language model and tokenizers. So make sure you use good tokenizer. If it is normal English utterances try using tokenizer_ spacy before ner_crf. Also try with ner_spacy



                As per my experience, 5 to 10 variations of utterances for each case gave a decent result to start with







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 24 '18 at 2:07









                Karthik SunilKarthik Sunil

                10117




                10117






























                    draft saved

                    draft discarded




















































                    Thanks for contributing an answer to Stack Overflow!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid



                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.


                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function () {
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53448063%2fconvention-for-creating-good-data-set-for-rasa-ner-crf%23new-answer', 'question_page');
                    }
                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    404 Error Contact Form 7 ajax form submitting

                    How to know if a Active Directory user can login interactively

                    TypeError: fit_transform() missing 1 required positional argument: 'X'