davidberenstein1957
commented
2 years ago Hello,
I feel this was resolved by installing the dependencies required by the package. Gensim >= 4.
Regards, David
On 5 Jun 2022, at 15:24, akshaydevml @.***> wrote:
Raised an issue earlier regarding the same problem and @davidberenstein1957 committed a fix and posted this code block as solution
import spacy from spacy import displacy
import concise_concepts
data = { "fruit": ["apple", "pear", "orange"], "vegetable": ["broccoli", "spinach", "tomato", "garlic", "onion", "beans"], "meat": ["beef", "pork", "fish", "lamb", "bacon", "ham", "meatball"], "dairy": ["milk", "butter", "eggs", "cheese", "cheddar", "yoghurt", "egg"], "herbs": ["rosemary", "salt", "sage", "basil", "cilantro"], "carbs": ["bread", "rice", "toast", "tortilla", "noodles", "bagel", "croissant"], }
text = """ Heat the oil in a large pan and add the Onion, celery and carrots. Then, cook over a medium–low heat for 10 minutes, or until softened. Add the courgette, garlic, red peppers and oregano and cook for 2–3 minutes. Later, add some oranges and chickens. """
model_path = "word2vec.model"
nlp = spacy.load("en_core_web_md", disable=["ner"]) nlp.add_pipe( "concise_concepts", config={ "data": data, "model_path": model_path, "ent_score": True, }, ) doc = nlp(text)
options = { "colors": { "fruit": "darkorange", "vegetable": "limegreen", "meat": "salmon", "dairy": "lightblue", "herbs": "darkgreen", "carbs": "lightbrown", }, "ents": ["fruit", "vegetable", "meat", "dairy", "herbs", "carbs"], }
ents = doc.ents for ent in ents: newlabel = f"{ent.label} ({float(ent.ent_score):.0%})" options["colors"][new_label] = options["colors"].get(ent.label.lower(), None) options["ents"].append(newlabel) ent.label = new_label doc.ents = ents
displacy.render(doc, style="ent", options=options)
However, I am still getting the 'Word2vec object is not iterable error'.
Could you please look into it?
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akshaydevml
prakhar251998
GenVr
Raised an issue earlier regarding the same problem and @davidberenstein1957 committed a fix and posted this code block as solution
import spacy from spacy import displacy
import concise_concepts
data = { "fruit": ["apple", "pear", "orange"], "vegetable": ["broccoli", "spinach", "tomato", "garlic", "onion", "beans"], "meat": ["beef", "pork", "fish", "lamb", "bacon", "ham", "meatball"], "dairy": ["milk", "butter", "eggs", "cheese", "cheddar", "yoghurt", "egg"], "herbs": ["rosemary", "salt", "sage", "basil", "cilantro"], "carbs": ["bread", "rice", "toast", "tortilla", "noodles", "bagel", "croissant"], }
text = """ Heat the oil in a large pan and add the Onion, celery and carrots. Then, cook over a medium–low heat for 10 minutes, or until softened. Add the courgette, garlic, red peppers and oregano and cook for 2–3 minutes. Later, add some oranges and chickens. """
model_path = "word2vec.model"
nlp = spacy.load("en_core_web_md", disable=["ner"]) nlp.add_pipe( "concise_concepts", config={ "data": data, "model_path": model_path, "ent_score": True, }, ) doc = nlp(text)
options = { "colors": { "fruit": "darkorange", "vegetable": "limegreen", "meat": "salmon", "dairy": "lightblue", "herbs": "darkgreen", "carbs": "lightbrown", }, "ents": ["fruit", "vegetable", "meat", "dairy", "herbs", "carbs"], }
ents = doc.ents for ent in ents: newlabel = f"{ent.label} ({float(ent.ent_score):.0%})" options["colors"][new_label] = options["colors"].get(ent.label.lower(), None) options["ents"].append(newlabel) ent.label = new_label doc.ents = ents
displacy.render(doc, style="ent", options=options)
However, I am still getting the 'Word2vec object is not iterable error'.
Could you please look into it?