uclnlp/cqd

Continuous Query Decomposition for Complex Query Answering in Incomplete Knowledge Graphs

cqd's Issues

2u/up queries reproduction with CQD @ KGReasoning

Since there is no issue board at https://github.com/pminervini/KGReasoning I thought I could write it here and tag @pminervini 😃

I'm trying to run CQD CO and Beam on the BetaE version of FB15k-237 and NELL-995 datasets using that repo, but for some reason, the numbers for union queries are very low.

After downloading the pre-trained models (fb15k-237-betae and nell-betae, respectively), I'm using the following commands:

python main.py -cuda --do_test --data_path FB15k-237-betae --cpu_num 1 --geo cqd --tasks "1p.2p.3p.2i.3i.ip.pi.2u.up" --checkpoint_path models/fb15k-237-betae -d 1000

python main.py -cuda --do_test --data_path NELL-betae --cpu_num 1 --geo cqd --tasks "1p.2p.3p.2i.3i.ip.pi.2u.up" --checkpoint_path models/nell-betae -d 1000

Other hyperparams are set as default ones (there is no info on when to put --cqd-sigmoid-scores or --cqd-normalize-scores, so I presume they should be turned off).

The numbers for 2u/up FB15k-237:

Test 2u-DNF MRR at step 99999: 0.005257
Test 2u-DNF HITS1 at step 99999: 0.001895
Test 2u-DNF HITS3 at step 99999: 0.004898
Test 2u-DNF HITS10 at step 99999: 0.010378
est 2u-DNF num_queries at step 99999: 5000.000000
Test up-DNF MRR at step 99999: 0.016857
Test up-DNF HITS1 at step 99999: 0.005590
Test up-DNF HITS3 at step 99999: 0.014344
Test up-DNF HITS10 at step 99999: 0.033338
Test up-DNF num_queries at step 99999: 5000.000000

And for NELL:

Test 2u-DNF MRR at step 99999: 0.007676
Test 2u-DNF HITS1 at step 99999: 0.004144
Test 2u-DNF HITS3 at step 99999: 0.006924
Test 2u-DNF HITS10 at step 99999: 0.014262
Test 2u-DNF num_queries at step 99999: 4000.000000
Test up-DNF MRR at step 99999: 0.023296
Test up-DNF HITS1 at step 99999: 0.010295
Test up-DNF HITS3 at step 99999: 0.022723
Test up-DNF HITS10 at step 99999: 0.045247
Test up-DNF num_queries at step 99999: 4000.000000

Is there anything missing or those are expected numbers for betae datasets?

P.S. Would be good to have an example of how to properly run CQD with KGReasoning in the example.sh :)

Answering queries with CQD Error

When I have trained the model, I followed the the path to answer the question but it showed that missing the entity2text.text .Could you please give some suggestions to slove the problems? thx!😊

Typo in model download instructions

Hi! I'm trying to reproduce the code following the instructions on the README and I found an error in the instructions.
In the instruction, a command for downloading and decompressing the model is provided. However, the decompressing instruction that follows does not refer to the models' file but to cqd-data. I've found that replacing the second line with

% tar xvf cqd-models.tgz

solves this issue :)

The procedure of the t-norms and neural link prediction

I sorry to say that I could't really understand the procedure of the t-norms and neural link prediction when I studying the codes of this module😔 ,could you give some pseudo codes, math formulas or illustrations about this module. thx!😘 Looking forward for your reply😊

Replicating the query explanations from Section 5.5/Figure 3

Hey thanks for releasing the code - is it possible to replicate your results from section 5.5 on explaining the answers to the queries?