I'm having a problem with Rasa_NLU giving me the wrong entity for an intent. An example is “How do I get to New York?” Where, I tagged the training data to name the entity “city”. In a different intent, it was tagged “destination”.
intent: check_weather
what is the weather in new york?
intent: get_directions
how do I get to new york?
I have a script that takes action on the intent returned and processes the entities. If I get back the get_directions intent, I’ll look in the json for the destination entity, but it has city instead. Using ner_crf, is there a way to de-emphasize entities in an intent, so that the classifier is biased to those that the intent was trained for? That is, the classifier would be weighted to giving a destination for get_directions, and a city for get_weather?
The typical answer I've found is to add more training examples. I'm up to 60 for each of the two intents I have, and it is still getting it wrong.
As of right now, you can only featurize/unfeaturize all entities for a certain intent. I can see that that's not really your use case since both intents require entities -- just different ones. There is currently a community PR open to add per-intent featurization of specific entities, so it will be available in the future.
Related
I am developing chatbot using Rasa for a Contract Manager Organisation. I am facing few issues and after reading a lot on the forums and Rasa blog, I am unable to conclude to a solution for this. I have several similar intents with similar examples like -
“inform_supplier_start_date” and “inform_contract_start_date”.
“inform_supplier_email” and “inform_customer_email” and “inform_reviewer_email”
Now the issue is, for both the categories of intents the example sentence in nlu.md is same. What I exactly mean is-
##intent:inform_suppler_start_date
-what is the supplier [Microsoft] (supplier_name) start date
-[EON Digital] (supplier_name) start date
##intent:inform_contract_start
1) start-date of [O2 Mobile phones] (contract_name)
2) [O2 Mobile phones] (contract_name) start date
The model isnt able to differentiate and identify the correct intent. It is getting confused and identifying the wrong intent, since the words in these intents are similar.
I need correct intents to be recognised ,so that accordingly, In custom action i can query the Database and get the corresponding result for supplier and contract.
I have many fields like this for which the example data and user queries will be same. For Example-
customer_email & supplier_email & reviewer_email
total_spend_contract & total_spend_supplier & total_spend_customer
contract_number_for_supplier & contract_number_of_contract & contract_number_organisation
What exactly I should be doing to get correct classification. One solution i am thinking of is merging the intents like “supplier_start_date” and "contract_start_date" as one “start_date” and check for the extracted entity inside custom actions in both supplier and contract database. But I dont think that would be proper usage of Natural Language.
Please Suggest, I shall be highly greatful for the same. Regards.
As the examples for your intents are very similar, the model will not be able to differentiate between them. Also the intent is actual the same, inform_suppler_start_date and inform_contract_start inform the bot about a start date. What kind of start date it is should be figured out via the entity recognition. So I would propose to merge the similar intents and check what the entity recognition detected as entities. Depending on whether a supplier or a contract was found, you can execute query A or B.
My question here is about Google Classroom's API.
When i am in the Classwork tab, I have a button to make posts; one option is "material". This type is not an assignement and does not have an assigned grade. This is a perfect concept: I can add materials, sorted by topics to my classwork page with no grades or assignments needed.
The problem for me is when i go to the api and look for that functionality, you can only see courseWork objects with "ASSIGNMENT" "SHORT_ANSWER_QUESTION" and "MULTIPLE_CHOICE_QUESTION" workTypes. All of those type have grades related, but no option exists for the "MATERIAL" type I can choose from the Create menu.
Nor do Material objects seem to exist in the API call.
Many other objects exist that I can find: coursework, announcements, topics, students, courses, teachers and others, but no material's object. Is this an omission? There is a "material" available but it's used for the attachments IN a CourseWork item, not the CourseWork itself.
Jose- I think I asked the same question as you but might have been clearer with the details. Perhaps check here if answers start to roll in. I have spent hours trying to interrogate objects to find this info with no luck.
Google Classroom API Create Material
I would have added this as a comment but my reputation doesn't allow it.
UPDATE: Huge thanks to #ziganotschka for this:
Indeed, there is a feature request for it already:
https://issuetracker.google.com/issues/127591179
I suggest you to give it a star to increase visibility and get updates
on the implementation status of the feature.
I have created several utterances in LUIS for an intent to create new meeting items in my application.
I have tagged the corresponding elements in the utterance to recognize the name of the invited person and the date / time of the meeting.
When I train the model and test it afterwards, date and time is recognized every time. Not so for the contactname. I have tried all possible things like adding the utterance as pattern, adding phrase lists, but no success.
What can I do, to make this work? Is there anythink I am missing?
If you're using simple entities, keep in mind that you'll need to train 10-15 utterances, and that there should be different names in all utterances. Using the same name repeatedly may cause faulty training.
I am working on a service that provides information about a few related entities, somewhat like a database. Suppose that there's calls to retrieve information about a school:
service MySchool {
rpc GetClassRoom (ClassRoomRequest) returns (ClassRoom);
rpc GetStudent (StudentRequest) returns (Student);
}
Now, suppose that I want to find out a class room's information, I'd receive a proto that looks like so:
message ClassRoom {
string id = 1;
string address = 2;
string teacher = 3;
}
Sometimes I also want to know all of the students of the classroom. I am struggling to think which is the better design pattern.
Option A) Add an extra rpc like so: rpc GetClassRoomStudents (ClassRoomRequest) returns (ClassRoomStudents), where ClassRoomStudents has a single field repeated Student students. This technique requires more than one call to get all the information that we want (and many if we wanted to know information for more than one classroom).
Option B) Add an extra repeated Student students field to the ClassRoom proto, and B') Fill it up only when necessary, or B") Fill it up whenever the server receives a GetClassRoom call. This may sometimes fetch extra information, or lead to ambiguity according to what fields are filled up.
I am not sure what's the best / most conventional way of dealing with this. How have some of you dealt with this?
There is no simple answer. It's a tradeoff between simplicity (option A) and performance (option B), and it depends on the situation which solution is best.
In general, I'd recommend to go with the simple solution first, unless your measurements demonstrate that it leads to performance issues. At that point, it's easy to add repeated Student students to ClassRoom and a field bool fetch_students [default=false] to ClassRoomRequest. Then clients are free to continue using the simple API, or choose to upgrade to the more performant API if they need to.
Note that this isn't specific to gRPC; the same issue is seen in REST APIs, and basically almost any request/response model.
I have an app in LUIS with one intent "Help" (appart from None) and when I test it with utterances that my intent does not cover (e.g "Hi man"), LUIS resolves to the "Help" intent... I have no utterances in "None" intent...
What should I do? Should I add all the utterances I don't want to match "Help" intent in "None"?
Should I need to know everything a user can ask to my bot which is not related with "Help"?
For me, that's not make sense at all... and I think that is exactly how LUIS works...
Intent are the action which we define, None is predefined Intent which come along with every LUIS model that you create , coming back to your problem. You have only define one intent i.e "help" so whenever LUIS gets the any query it will show the highest scoring intent i.e. "help". whenever you create an intent make to sure to save at least 5-6 co-related utterance, so that LUIS can generate a pattern out of it 'more you define co-related utterance better accuracy of result you will get'
if you want LUIS to respond on "HI man" create a new intent 'greet' save some utterance let LUIS do the remaining task, lastly about None intent If any user input 'asdsafdasdsfdsf' string like this. Your bot should be able to handle it respond accordingly like 'this asdsafdasdsfdsf is irrelevant to me' in simple term 'any irregular action that user want bot to perform come under none intent' i hope this will help
You can check the score of the Luis intent and then accordingly send the default response from code. For the utterances which are configured will have a greater score. Also, Luis app shud be balanced in terms of utterances configured as there is not a defined way that u can point utterances to None intent. Please check this link for best practices.
https://learn.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-best-practices. Also to highlight Luis does not work in terms of keyword matching to the utterances which you have configured. It works in terms of data you add in Luis in respective intents.