# discourse analysis recipe **URL:** \ **Category:** Uncategorized\ **Tags:** enhancement, usage, done, relations\ **Created:** [April 27, 2020, 3:06pm UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834 "2020-04-27T15:06:57Z")\ **Posts on this page:** 6\ **Page:** 1
**Author:** ![jcbmyrstn](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/jcbmyrstn/32/1352_2.png) [@jcbmyrstn](https://support.prodi.gy/u/jcbmyrstn)\ **Post date:** [April 27, 2020, 3:06pm UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834/1 "2020-04-27T15:06:57Z")
Hello All, I have a question about a recipe, but I wanted to introduce myself first. I am exploring right now both the library and prodigy for use in a university research project about social networks in the ancient world. I’m working on a corpus of biographies of ancient philosophers and are trying to extract from that corpus who was teacher of whom and the migration routes of those individuals: who moved from where to where to study with whom. (For now, I am using English translations but am planning to conduct the research in ancient Greek if we can build with my students an ancient Greek model for spacy) We were using the matcher with a language model I retrained with prodigy, but we couldn’t capture much due to the complexity of the literary texts in the corpus. We are looking now at the train\_intent\_parser.py example in spacy, which is used to predict trees over whole documents. We are considering a similar approach to extract relations between people and places in our corpus. What would be the existing prodigy recipe to train such a parser? Or which one could be adapted for our purposes? Thanks, Jacobo ---
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [April 28, 2020, 8:20pm UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834/2 "2020-04-28T20:20:53Z")
Hi! That's an interesting use case 🙂 How you set up an annotation workflow kinda depends on the specifics of your dependency scheme. If you can narrow down the possible candidates that are part of a relationship you could stream in pairs and then use the `choice` interface to select the relationships between them. For instance, if you have an entity recognizer or rule-based process that extracts names and two people are mentioned together, you can show both mentions, and select a label for the relation. A similar(ish) use case came up in the following thread the other day and it inspired me to dig a bit deeper and try out some ideas we've had for a manual interface for labelling complex relationships, and even relationships and spans at the same time. You can see some early screenshots here: > [@Create training and testing data for triples](https://support.prodi.gy/t/create-training-and-testing-data-for-triples/2734/6): > > Yes, I definitely see the problem here, hmm thinking One option would be to start by doing the 75% first and then deal with the remaining 25% with multiple relations separately. In general, Prodigy avoids anything related to having the annotator modify the actual examples to annotate (e.g. duplicate examples) because that's something that should typically be decided on the development level. But this case is kind of an exception here. One option could be to set "instant\_submit": true, which w… It turned out to be a really powerful interface and we'll be introducing it in Prodigy v1.10, along with some recipes for fully manual relation annotation, model-assisted dependency parsing annotation and coreference resolution. So this is probably also going to be a good fit for what you're trying to do. ---
**Author:** ![adamkgoldfarb](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/adamkgoldfarb/32/741_2.png) [@adamkgoldfarb](https://support.prodi.gy/u/adamkgoldfarb)\ **Post date:** [April 29, 2020, 12:41am UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834/3 "2020-04-29T00:41:11Z")
Sign me up for the coreference resolution beta! ---
**Author:** ![jcbmyrstn](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/jcbmyrstn/32/1352_2.png) [@jcbmyrstn](https://support.prodi.gy/u/jcbmyrstn)\ **Post date:** [April 29, 2020, 7:13pm UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834/4 "2020-04-29T19:13:36Z")
Hi Ines, I will be looking forward to the next release. Thanks, Jacobo ---
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [May 11, 2020, 10:07am UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834/5 "2020-05-11T10:07:28Z")
@adamkgoldfarb @jcbmyrstn Update 🎉 > [@sparkleslink Beta testers wanted: new manual dependencies & relations UI (v1.10)](https://support.prodi.gy/t/beta-testers-wanted-new-manual-dependencies-relations-ui-v1-10/2893): > > I already mentioned this briefly in the call for [image UI beta testers](https://support.prodi.gy/t/beta-testers-wanted-new-manual-image-ui-v1-10/2840): the upcoming Prodigy v1.10 will feature a completely new interface and a suite of recipes for efficient relation and dependency annotation tada We're especially excited about this one, since it's been one of the missing features in Prodigy and it took a while to develop efficient solutions for the various challenges involved. Features include manually annotate labelled dependencies and relationships between words and phr… ---
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [June 17, 2020, 5:38pm UTC](https://support.prodi.gy/t/discourse-analysis-recipe/2834/6 "2020-06-17T17:38:08Z")
Just released Prodigy v1.10, which includes the new `relations` UI and different workflows for annotating relations, including a `rel.manual` recipe for full custom semi-automated annotation. > [@rocket Out now: Prodigy v1.10 (plus new video!)](https://support.prodi.gy/t/out-now-prodigy-v1-10-plus-new-video/3030): > > Prodigy v1.10 is out now tada And it includes a bunch of cool new features, including dependency and relation annotation, audio and video annotation, an enhanced manual image UI, more settings for NER annotation, including character-based highlighting and a cool example workflow for creating training data for fine-tuning transformer models, new recipe callbacks for validating answers at runtime and for modifying examples before the database, new settings for UI customisation, and lots more! Th…