Comments (20)
Thank you @abhinavralhan for sharing the bug and thanks @gyanesh-m for fixing it.
from gsoc.
@mommi84 is the better person to explain that :)
from gsoc.
@abhinavralhan Hi! I added a link in the project description.
from gsoc.
@abhinavralhan Hi, I faced a similar issue. The problem is due to incorrect data directory passed to ask.sh. Currently it is data/monument_300_model. You need to change the input directory for ask.sh to data/monument_300 .
from gsoc.
Added example of successful project proposal. Once ready, please invite my username at gmail dot com to your proposal document.
from gsoc.
The GSoC 2018 student applications are officially open! Please elaborate your proposal in a Google doc. When you're done, share it with my username at gmail.com, so I can invite also the other mentors. Deadline: March 27.
from gsoc.
Sounds interesting! I will have a look on this after my exams.
from gsoc.
@mgns Hi. This sounds very interesting to me. I had a few queries to ask though.
from gsoc.
You are welcome to ask them here.
from gsoc.
@RicardoUsbeck Yeah so I was attempting the Warmup tasks. Can you please explain how should I attempt the second task?
from gsoc.
@mommi84 a little problem with the last inference bit. I got past most problems except this one I cannot understand. So I ran the command below, but for some reason vocab file is not getting generated. I'm guessing it has to do with something in the ask.sh file.
sudo sh ask.sh data/monument_300_model "where is edward vii monument located in?"
Traceback (most recent call last):
File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main
"main", fname, loader, pkg_name)
File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/home/abhinavralhan/Desktop/os/NSpM/nmt/nmt/nmt.py", line 495, in
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 124, in run
_sys.exit(main(argv))
File "/home/abhinavralhan/Desktop/os/NSpM/nmt/nmt/nmt.py", line 488, in main
run_main(FLAGS, default_hparams, train_fn, inference_fn)
File "/home/abhinavralhan/Desktop/os/NSpM/nmt/nmt/nmt.py", line 452, in run_main
hparams = create_or_load_hparams(out_dir, default_hparams, flags.hparams_path)
File "/home/abhinavralhan/Desktop/os/NSpM/nmt/nmt/nmt.py", line 418, in create_or_load_hparams
hparams = extend_hparams(hparams)
File "/home/abhinavralhan/Desktop/os/NSpM/nmt/nmt/nmt.py", line 350, in extend_hparams
unk=vocab_utils.UNK)
File "nmt/utils/vocab_utils.py", line 66, in check_vocab
raise ValueError("vocab_file does not exist.")
ValueError: vocab_file does not exist.
train_prefix=None
dev_prefix=None
test_prefix=None
out_dir=../data/monument_300_model_model
ANSWER IN SPARQL SEQUENCE:
cat: output.txt: No such file or directory
from gsoc.
@mommi84 Hi, I have been trying to build some queries for dbo:EducationalInstitution class and I had a doubt related to query templates. In all the examples mentioned in annotations_monument.csv, the initial statement
?a a dbo:Monument
was never used. Is it because you have already specified the domain for <A> in first column. Also, If I plan to use the initial statement for my example class in query template, will it be fine ?
from gsoc.
Hey @gyanesh-m,
No you don't need to explicitly add that. prepare_generator_query adds the "initial statement" to the generator queries.
from gsoc.
@piyush96chawla Oh , thanks.
from gsoc.
Interesting project! I have started working on it already.
from gsoc.
Only 6 days to go!
Please share your document with us now, if you would like to have some feedback from the mentors before the final submission to the GSoC console.
from gsoc.
@mommi84 I have completed my warmup task by training the NSpM model on class dbo:Garden.
I have experience in QA, deep learning, and I really appreciate and like the idea of a Neural QA model. What do you suggest I should do next in order to get ready to write a proposal? Sorry for such a late request for help.
from gsoc.
@amanmehta-maniac Great. Please elaborate your view of the project and your findings in a Google document and share it with me at gmail.com. Use this one as a reference for a good proposal. Send it out on Sunday 25th at the latest, so we can give you some feedback.
from gsoc.
@mommi84, there are around 770 total number of DBpedia classes and hence what would be a realistic 'X', where X is the number of classes that I will train this NN for during the GSoC tenure.
Also, another matter of concern is, will I be getting access to any server, because this project involves training NN which is highly CPU intensive and takes order of hours on 64 core-CPU and 512 GB RAM machine.
from gsoc.
@amanmehta-maniac We expect to have one final QA model, not as many as the number of classes. Moreover, these 770 classes are organized in a taxonomy. We will likely be able to grant the student access to our servers upon availability for a limited time (up to 14 days in a row). Of course, additional hardware provided by the student's institution is welcome.
from gsoc.
Related Issues (20)
- Setup a YASGUI interface for DBpedia
- Find 10 or 100 errors in DBpedia HOT 4
- DBpedia Embeddings for Out-Of-Vocabulary Resources HOT 20
- Recurrent Neural Network Embedding for Knowledge-Base Completion
- Automatic schema alignment between DBpedia mappings in different languages HOT 12
- Tool to generate RDF from DBpedia abstracts (natural language text) HOT 6
- A Neural QA Model for DBpedia (GSoC 2019) HOT 19
- Extending Extraction Framework with Citations, Commons and Lexemes Extractors
- Predicate Detection using Word Embeddings for Question Answering over Linked Data HOT 10
- A Multilingual Neural RDF Verbalizer HOT 16
- Explainable Knowledge Discovery on DBpedia HOT 13
- Pay-As-You-Go Quality Evaluation of the DBpedia Resources HOT 13
- Dataset recommendation system in databus for several analysis. Integrating chatbot with the main website and DBpedia databus to get the dataset information. HOT 2
- Golden standard and quality tool for DBpedia types
- Improve the Mapping experience, possibly with gamification (use the new RML mapping UI) HOT 4
- Workflow for linking external datasets HOT 1
- Fusing the List Extractor and the Table Extractor HOT 8
- Mapping Generation from Resource Descriptions HOT 2
- Run Extraction Framework HOT 2
- Extend the Extraction Framework for your language HOT 4
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from gsoc.