Comments (2)
kosugi11037
commented on September 7, 2024
Hi, sorry for late reply. Entity descriptions often contain entity's name. And entity descriptions are richer in semantic information than entity names. Intuitively, concatenating entity name with entity description as part of model input may have similar effects to only using entity description.
(And I try to use concatenating entity name with entity description as part of model input, the result is really similar.)
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KartavyaKothari
commented on September 7, 2024
Thanks! got it
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Related Issues (17)
- Basic_Bert_Unit_model 训练问题 HOT 2
- Description data是如何提取的 HOT 3
- 关于DWY100K数据集 HOT 5
- Why aggregation operation by RBF? HOT 1
- Can you tell me about the description of DWY100k? HOT 1
- result = self.forward(*input, **kwargs) File "/data/my_project/nlp_text/nlp_models/bert-int-master/basic_bert_unit/Basic_Bert_Unit_model.py", line 20, in forward cls_vec = sequence_output[:,0] HOT 1
- Neighboring relation mask matrix的计算问题
- 运行basic_bert_unit时遇到的问题
- 运行interaction_model.py遇到问题，没有"../data/dbp15k/ja_en/attribute_similarity_feature.pkl"文件
- Basic_Bert_Unit_model train-test相似度以及epoch-loss HOT 3
- Attribute-view Interactions的问题 HOT 3
- Upload pre-trained BERT unit models HOT 1
- What are hardware requirements for training bert-int from scratch with/without cuda? HOT 2
- Results aren't matching the paper results HOT 1
- Could you share data conversion scripts / rules you used? HOT 3
- 提供的预训练模型无法正常使用。 HOT 3
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