Update spacy pipeline to 3.3.1

README.md

@@ -14,72 +14,72 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8607281725
+      value: 0.847826087
     - name: NER Recall
       type: recall
-      value: 0.8561884669
+      value: 0.8570675105
     - name: NER F Score
       type: f_score
-      value: 0.858452318
+      value: 0.8524217521
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9638738696
+      value: 0.9677018039
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9649265515
+      value: 0.9675104072
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9324337257
+      value: 0.9386544167
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9681370204
+      value: 0.9716773514
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.8211578415
+      value: 0.8069939475
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.7476698484
+      value: 0.736004483
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9788182832
+      value: 0.9821029083
 ---
 Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner
 
 | Feature | Description |
 | --- | --- |
 | **Name** | `hu_core_news_lg` |
-| **Version** | `3.3.0` |
+| **Version** | `3.3.1` |
 | **spaCy** | `>=3.3.0,<3.4.0` |
-| **Default Pipeline** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lemmatizer`, `parser`, `ner` |
-| **Components** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lemmatizer`, `parser`, `ner` |
+| **Default Pipeline** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lookup_lemmatizer`, `lemmatizer`, `lemma_smoother`, `parser`, `ner` |
+| **Components** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lookup_lemmatizer`, `lemmatizer`, `lemma_smoother`, `parser`, `ner` |
 | **Vectors** | -1 keys, 200000 unique vectors (300 dimensions) |
 | **Sources** | [UD Hungarian Szeged](https://universaldependencies.org/treebanks/hu_szeged/index.html) (Richárd Farkas, Katalin Simkó, Zsolt Szántó, Viktor Varga, Veronika Vincze (MTA-SZTE Research Group on Artificial Intelligence))<br />[NYTK-NerKor Corpus](https://github.com/nytud/NYTK-NerKor) (Eszter Simon, Noémi Vadász (Department of Language Technology and Applied Linguistics))<br />[hunNERwiki](http://hlt.sztaki.hu/resources/hunnerwiki.html) (Eszter Simon, Dávid Márk Nemeskey (HLT Group, Budapest University of Technology and Economics))<br />[Szeged NER Corpus](https://rgai.inf.u-szeged.hu/node/130) (György Szarvas, Richárd Farkas, László Felföldi, András Kocsor, János Csirik (MTA-SZTE Research Group on Artificial Intelligence))<br />[Webcorpuswiki word2vec model](https://github.com/oroszgy/hunlp-resources/releases/tag/webcorpuswiki_word2vec_v0.1) (György Orosz) |
 | **License** | `cc-by-sa-4.0` |
@@ -108,18 +108,18 @@ Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morpholog
 | `TOKEN_P` | 99.86 |
 | `TOKEN_R` | 99.93 |
 | `TOKEN_F` | 99.89 |
-| `SENTS_P` | 97.99 |
-| `SENTS_R` | 97.77 |
-| `SENTS_F` | 97.88 |
-| `TAG_ACC` | 96.39 |
-| `POS_ACC` | 96.49 |
-| `MORPH_ACC` | 93.24 |
-| `MORPH_MICRO_P` | 96.86 |
-| `MORPH_MICRO_R` | 95.85 |
-| `MORPH_MICRO_F` | 96.35 |
-| `LEMMA_ACC` | 96.81 |
-| `DEP_UAS` | 82.12 |
-| `DEP_LAS` | 74.77 |
-| `ENTS_P` | 86.07 |
-| `ENTS_R` | 85.62 |
-| `ENTS_F` | 85.85 |
+| `SENTS_P` | 97.77 |
+| `SENTS_R` | 97.55 |
+| `SENTS_F` | 97.66 |
+| `TAG_ACC` | 96.31 |
+| `POS_ACC` | 96.34 |
+| `MORPH_ACC` | 92.89 |
+| `MORPH_MICRO_P` | 96.28 |
+| `MORPH_MICRO_R` | 95.58 |
+| `MORPH_MICRO_F` | 95.93 |
+| `LEMMA_ACC` | 97.25 |
+| `DEP_UAS` | 81.13 |
+| `DEP_LAS` | 74.49 |
+| `ENTS_P` | 87.15 |
+| `ENTS_R` | 83.72 |
+| `ENTS_F` | 85.40 |

config.cfg

@@ -1,6 +1,7 @@
 [paths]
-parser_model = "models/hu_core_news_lg-parser-3.3.0/model-best"
-ner_model = "models/hu_core_news_lg-ner-3.3.0/model-best"
+parser_model = "models/hu_core_news_lg-parser-3.3.1/model-best"
+ner_model = "models/hu_core_news_lg-ner-3.3.1/model-best"
+lemmatizer_lookups = "models/hu_core_news_lg-lookup-lemmatizer-3.3.1"
 train = null
 dev = null
 vectors = null
@@ -12,7 +13,7 @@ gpu_allocator = null
 
 [nlp]
 lang = "hu"
-pipeline = ["tok2vec","senter","tagger","morphologizer","lemmatizer","parser","ner"]
+pipeline = ["tok2vec","senter","tagger","morphologizer","lookup_lemmatizer","lemmatizer","lemma_smoother","parser","ner"]
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
 disabled = []
 before_creation = null
@@ -22,6 +23,9 @@ batch_size = 1000
 
 [components]
 
+[components.lemma_smoother]
+factory = "hu.lemma_smoother"
+
 [components.lemmatizer]
 factory = "trainable_lemmatizer"
 backoff = "orth"
@@ -51,6 +55,11 @@ depth = 4
 window_size = 2
 maxout_pieces = 5
 
+[components.lookup_lemmatizer]
+factory = "hu.lookup_lemmatizer"
+scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
+source = ${paths.lemmatizer_lookups}
+
 [components.morphologizer]
 factory = "morphologizer"
 extend = false

hu_core_news_lg-any-py3-none-any.whl

@@ -1,3 +1,3 @@
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-size 401139364
+oid sha256:da2b5830c7953203b64049813cbb0f4a181aa47be42744aa800af2fe3a22f0aa
+size 403094603

lemmatizer/model

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f8a0dd8dc58167511bbcf3998dc1eea156915c72cdbe57f070ab1dabbf1a9b6b
+oid sha256:58b56ab3836952a8e612a411c2a1958630e46569225dce1cabb138e7fdc17658
 size 64058360

lookup_lemmatizer/lookups.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c7aaa1cfd45a0afd57ada8ccc690ee182485a151bdb133b7b8c9276647ab9e60
+size 2745978

meta.json

@@ -1,7 +1,7 @@
 {
   "lang":"hu",
   "name":"core_news_lg",
-  "version":"3.3.0",
+  "version":"3.3.1",
   "description":"Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner",
   "author":"SzegedAI, MILAB",
   "email":"[email protected]",
@@ -1188,6 +1188,9 @@
       "Case=Dat|Number=Plur|POS=PRON|Person=1|PronType=Prs",
       "Case=Acc|Number=Plur|Number[psor]=Sing|POS=PROPN|Person[psor]=3",
       "Case=All|Number=Sing|Number[psed]=Sing|POS=PRON|Person=3|PronType=Tot"
+    ],
+    "lookup_lemmatizer":[
+
     ],
     "parser":[
       "ROOT",
@@ -1246,7 +1249,9 @@
     "senter",
     "tagger",
     "morphologizer",
+    "lookup_lemmatizer",
     "lemmatizer",
+    "lemma_smoother",
     "parser",
     "ner"
   ],
@@ -1255,7 +1260,9 @@
     "senter",
     "tagger",
     "morphologizer",
+    "lookup_lemmatizer",
     "lemmatizer",
+    "lemma_smoother",
     "parser",
     "ner"
   ],
@@ -1267,85 +1274,85 @@
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-    "tag_acc":0.9638738696,
-    "pos_acc":0.9649265515,
-    "morph_acc":0.9324337257,
-    "morph_micro_p":0.9686020758,
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-    "morph_micro_f":0.9635181545,
+    "sents_f":0.9821029083,
+    "tag_acc":0.9677018039,
+    "pos_acc":0.9675104072,
+    "morph_acc":0.9386544167,
+    "morph_micro_p":0.9693278037,
+    "morph_micro_r":0.9642458101,
+    "morph_micro_f":0.9667801284,
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@@ -1353,9 +1360,9 @@
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@@ -1363,114 +1370,114 @@
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