Commit 44c98cdf authored by Deyan Ginev's avatar Deyan Ginev
Browse files

arxmliv embeddings 08.2018, now available

parent 1c6c6b5d
......@@ -18,7 +18,7 @@ Access is restricted to [SIGMathLing members](/member/) under the
articles, the right of distribution was only given (or assumed) to arXiv itself.
### Contents
- A 5 billion token model for the arXMLiv 08.2018 dataset
- An 11.5 billion token model for the arXMLiv 08.2018 dataset, including subformula lexemes
- `token_model.zip`
- 300 dimensional GloVe word embeddings for the arXMLiv 08.2018 dataset
- `glove.arxmliv.5B.300d.zip` and `vocab.arxmliv.zip`
......@@ -30,26 +30,26 @@ articles, the right of distribution was only given (or assumed) to arXiv itself.
subset | documents | paragraphs | sentences |
-----------|----------:|-----------:|------------:|
no_problem | | | |
warning | | | |
error | | | |
complete | | | |
subset | words |formulas | inline cite | numeric literals |
-----------|--------------:|-----------:|------------:|-----------------:|
no_problem | | | | |
warning | | | | |
error | | | | |
complete | | | | |
no_problem | 137,864 | 4,646,203 | 21,533,963 |
warning | 705,095 | 45,797,794 | 183,246,777 |
error | 389,225 | 26,759,524 | 99,641,978 |
complete | 1,232,184 | 77,203,521 | 304,422,718 |
subset | words | formulas | inline cite | numeric literals |
-----------|--------------:|-----------: |------------:|-----------------:|
no_problem | 430,217,995 | 20,910,732 | 3,709,520 | 11,177,753 |
warning | 3,175,663,430 | 281,832,412 | 25,337,574 | 83,606,897 |
error | 1,731,971,035 | 153,186,264 | 13,145,561 | 43,399,720 |
complete | 5,337,852,460 | 455,929,408 | 42,192,655 | 138,184,370 |
#### GloVe Model Statistics
subset | tokens | unique words | unique words (freq 5+ )
-----------|--------------:|-------------:|-----------------------:
no_problem | | |
warning | | |
error | | |
complete | | |
subset | tokens | unique words | unique words (freq 5+ )
-----------|--------------: |-------------:|-----------------------:
no_problem | 622,968,267 | 715,433 | 219,304
warning | 7,203,536,205 | 3,478,235 | 666,317
error | 3,691,805,321 | 2,444,532 | 574,467
complete | 11,518,309,793 | 5,285,379 | 1,000,295
### Citing this Resource
......@@ -60,7 +60,7 @@ Please cite the main dataset when using the word embeddings, as they are generat
([SIGMathLing members](/member/) only)
### Generated via
- [llamapun 0.2](https://github.com/KWARC/llamapun/releases/tag/0.2),
- [llamapun 0.2.0](https://github.com/KWARC/llamapun/releases/tag/0.2.0),
- [GloVe 1.2, 2018](https://github.com/stanfordnlp/GloVe/tree/07d59d5e6584e27ec758080bba8b51fce30f69d8)
### Generation Parameters
......@@ -73,12 +73,12 @@ Please cite the main dataset when using the word embeddings, as they are generat
```
* [llamapun v0.2](https://github.com/KWARC/llamapun/releases/tag/0.2), `corpus_token_model` example used for token model extraction
* used llamapun math-aware sentence and word tokenization
* processed logical paragraphs only (excluded non-textual modalities, e.g. tables, figures and their captions, bibliographies)
* marked up formulas replaced with `mathformula` token
* processed logical paragraphs only (excluded non-textual modalities, e.g. tables, figures and their captions, bibliographies, as well as abstracts)
* excluded paragraphs containing latexml errors (marked via a `ltx_ERROR` HTML class)
* used llamapun math-aware sentence and word tokenization, with subformula math lexemes
* marked up inline citations replaced with `citationelement` token
* numeric literals replaced with `NUM` token
* ignored sentences with unnaturally long words (>30 characters) - almost always due to latexml conversion errors
* numeric literals replaced with `NUM` token (both in text and formulas)
* ignored sentences with unnaturally long words (>25 characters) - almost always due to latexml conversion errors
* [GloVe repository at sha 07d59d](https://github.com/stanfordnlp/GloVe/tree/07d59d5e6584e27ec758080bba8b51fce30f69d8)
* build/vocab_count -min-count 5
* build/cooccur -memory 32.0 -window-size 15
......@@ -89,24 +89,24 @@ Please cite the main dataset when using the word embeddings, as they are generat
#### GloVe in-built evaluation (non-expert tasks e.g. language, relationships, geography)
1. no_problem
* Total accuracy:
* Highest score:
* Total accuracy: 27.47% (4028/14663)
* Highest score: "gram3-comparative.txt", 75.30% (1003/1332)
2. warning
* Total accuracy:
* Highest score:
* Total accuracy: 31.97% (5351/16736)
* Highest score: "gram3-comparative.txt", 77.40% (1031/1332)
3. error
* Total accuracy:
* Highest score:
* Total accuracy: 29.67% (4910/16549)
* Highest score: "gram3-comparative.txt", 72.75% (969/1332)
4. complete
* Total accuracy:
* Highest score:
* Total accuracy: 35.48% (6298/17750)
* Highest score: "gram3-comparative.txt", 76.65% (1021/1332)
5. demo baseline: text8 demo (first 100M characters of Wikipedia)
* Total accuracy:
* Highest score:
* Total accuracy: 23.62% (4211/17827)
* Highest score: "gram6-nationality-adjective.txt", 58.65% (892/1521)
**Evaluation note:** These in-built evlauation runs are provided as a sanity check that the generated GloVe models pass a basic baseline against the non-expert tasks in the default GloVe suite.
One would need a scienctific discourse tailored set of test cases to evaluate the arXiv-based models competitively.
......@@ -114,37 +114,187 @@ One would need a scienctific discourse tailored set of test cases to evaluate th
#### Measuring word analogy
In a cloned GloVe repository, start via:
```
python eval/python/word_analogy.py --vocab_file vocab.arxmliv.txt --vectors_file glove.arxmliv.5B.300d.txt
python2 eval/python/word_analogy.py --vocab_file vocab.arxmliv.txt --vectors_file glove.arxmliv.11B.300d.txt
```
1. `abelian` is to `group` as `disjoint` is to `?`
* Top hit:
* Top hit: `union`, cosine distance `0.653377`
2. `convex` is to `concave` as `positive` is to `?`
* Top hit:
* Top hit: `negative`, cosine distance `0.786877`
3. `finite` is to `infinte` as `abelian` is to `?`
* Top hit:
* Top hit: `nonabelian`, cosine distance `0.676042`
4. `quantum` is to `classical` as `bottom` is to `?`
* Top hit:
* Top hit: `top`, cosine distance `0.734896`
5. `eq` is to `proves` as `figure` is to `?`
* Top hit:
* Top hit: `showing`, cosine distance `0.668502`
6. `italic_x` is to `italic_y` as `italic_a` is to `?`
* Top hit: `italic_b`, cosine distance `0.902608`
#### Nearest word vectors
In a cloned GloVe repository, start via:
```
python eval/python/distance.py --vocab_file vocab.arxmliv.txt --vectors_file glove.arxmliv.5B.300d.txt
python2 eval/python/distance.py --vocab_file vocab.arxmliv.txt --vectors_file glove.arxmliv.11B.300d.txt
```
1. **lattice**
```
Word: lattice Position in vocabulary: 488
Word Cosine distance
---------------------------------------------------------
lattices 0.853103
triangular 0.637767
honeycomb 0.626426
crystal 0.624397
finite 0.614720
spacing 0.603067
```
2. **entanglement**
```
Word: entanglement Position in vocabulary: 1568
Word Cosine distance
---------------------------------------------------------
entangled 0.780425
multipartite 0.730968
concurrence 0.691708
negativity 0.649595
tripartite 0.647623
quantum 0.640395
fidelity 0.640285
teleportation 0.616797
discord 0.613752
entropy 0.612341
bipartite 0.608034
coherence 0.606859
nonlocality 0.601337
```
3. **forgetful**
```
Word: forgetful Position in vocabulary: 11740
Word Cosine distance
---------------------------------------------------------
functor 0.723472
functors 0.656184
morphism 0.598965
```
4. **eigenvalue**
```
Word: eigenvalue Position in vocabulary: 1448
Word Cosine distance
---------------------------------------------------------
eigenvalues 0.893073
eigenvector 0.768380
eigenvectors 0.765241
eigenfunction 0.754222
eigenfunctions 0.686141
eigenspace 0.666098
eigen 0.641422
matrix 0.616723
eigenmode 0.613117
eigenstate 0.612188
laplacian 0.611396
largest 0.606122
smallest 0.605342
eigenmodes 0.604839
```
5. **riemannian**
```
Word: riemannian Position in vocabulary: 2285
Word Cosine distance
---------------------------------------------------------
manifolds 0.765827
manifold 0.760806
metric 0.719817
finsler 0.687826
curvature 0.676100
ricci 0.664770
metrics 0.660804
riemmanian 0.651666
euclidean 0.644686
noncompact 0.643878
conformally 0.638984
riemanian 0.633814
kahler 0.632680
endowed 0.622035
submanifold 0.613868
submanifolds 0.612716
geodesic 0.604488
```
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