| { |
| "datasets": { |
| "xnli-eu-native": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/eu/xnli-eu-native.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-var": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/eu/xnli-eu-var.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-es-native": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/es/xnli-eu2es-native.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-es-var": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/es/xnli-es-var.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-en": { |
| "data_path": "/tartalo01/users/jbengoetxea004/phd/xnli-paraphrasing/xnli-var-decoders/scripts/parquet-con/xnli-en-test.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-es": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/es/xnli-es-original.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/eu/xnli-eu-original.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-var-no-rep": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/eu/xnli-native-var-eu-NO-REPETITION.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-var-less-gip": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/eu/xnli-native-var-eu-less-gip.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-var-less-biz": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/eu/xnli-native-var-eu-less-biz.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-es-var-no-rep": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/es/xnli-native-var-es-no-rep.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-biz": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/test_expanded/xnli-eu-test-bizkaiera-done.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-gip": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/test_expanded/xnli-eu-test-gipuzkera-done.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-naf": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/test_expanded/xnli-eu-test-nafar-lapurtera-done.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-nat-biz": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/test_expanded/xnli-eu-native-bizkaieraz-done.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-nat-gip": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/test_expanded/xnli-eu-native-gipuzkera-done.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| }, |
| "xnli-eu-nat-naf": { |
| "data_path": "/scratch/jbengoetxea/phd/XNLIvar/data/test_expanded/xnli-eu-native-nafar-lapurtera-done.tsv", |
| "data_path_paraphrase": "", |
| "prem_col": "premise", |
| "hyp_col": "hypothesis", |
| "label_col": "label", |
| "prompts": ["trilabel", "qa-zero", "qa-few"] |
| } |
| }, |
| "models": { |
| "llama3instruct8": "meta-llama/Meta-Llama-3-8B-Instruct", |
| "llama3instruct70": "meta-llama/Meta-Llama-3-70B-Instruct", |
| "gemmainstruct9": "google/gemma-2-9b-it", |
| "gemmainstruct27": "google/gemma-2-27b-it", |
| "latxainstruct70": "HiTZ/Latxa-Llama-3.1-70B-Instruct", |
| "llama3base70": "meta-llama/Meta-Llama-3.1-70B" |
| }, |
| "prompts": { |
| "trilabel": { |
| "nli-zero": { |
| "preffix": "Please, answer in one word, with one of the following labels: <entailment>, <contradiction> or <neutral> Use exactly one of these three labels.", |
| "label_mapping": { |
| "entailment": "entailment", |
| "contradiction": "contradiction", |
| "neutral": "neutral" |
| } |
| }, |
| "nli-few": { |
| "preffix": "Say which is the inference relationship between these two sentences. Please, answer in one word, with one of the following labels: <entailment>, <contradiction> or <neutral> Use exactly one of these three labels. Here you have some examples: Postal Service were to reduce delivery frequency -> The postal service could deliver less frequently: <entailment>. This elegant spa town on the edge of the Lac du Bourget has offered cures for rheumatism and other ailments for centuries -> The town was only established in the past fifty years: <contradiction>. And while we allow people to give a kidney to their child , we do not allow them to donate their heart -> You can't always donate organs to your child: <neutral>. " , |
| "label_mapping": { |
| "entailment": "entailment", |
| "contradiction": "contradiction", |
| "neutral": "neutral" |
| } |
| }, |
| "qa-zero": { |
| "preffix": "Are these two sentences entailed, contradicted or undetermined to each other? Please, answer in one word, with one of the following labels: <entailment>, <contradiction> or <neutral> Use exactly one of these three labels.", |
| "label_mapping": { |
| "entailment": "entailment", |
| "contradiction": "contradiction", |
| "neutral": "neutral" |
| } |
| }, |
| "qa-few": { |
| "preffix": "Are these two sentences entailed, contradicted or undetermined to each other? Please, answer in one word, with one of the following labels: <entailment>, <contradiction> or <neutral> Use exactly one of these three labels. Here you have some examples: Postal Service were to reduce delivery frequency -> The postal service could deliver less frequently: <entailment>. This elegant spa town on the edge of the Lac du Bourget has offered cures for rheumatism and other ailments for centuries -> The town was only established in the past fifty years: <contradiction>. And while we allow people to give a kidney to their child , we do not allow them to donate their heart -> You can't always donate organs to your child: <neutral>.", |
| "label_mapping": { |
| "entailment": "entailment", |
| "contradiction": "contradiction", |
| "neutral": "neutral" |
| } |
| }, |
| "chain": { |
| "preffix": "You are an expert linguist and your task is to annotate sentences for the task of Natural Language Inference. This task consists in determining if a first sentence (premise) entails, contradicts or does not entail nor contradict the second sentence (hypothesis). Please, answer in one word, with one of the following labels: <entailment>, <contradiction> or <neutral> \n Use exactly one of these three labels \n Here you have a few examples:\n Premise: Postal Service were to reduce delivery frequency. \n Hypothesis: The postal service could deliver less frequently. \n Answer: <entailment> \n Premise: This elegant spa town on the edge of the Lac du Bourget has offered cures for rheumatism and other ailments for centuries. \n Hypothesis: The town was only established in the past fifty years. \n Answer: <contradiction> \n Premise: And while we allow people to give a kidney to their child , we do not allow them to donate their heart. \n Hypothesis: You can't always donate organs to your child. \n Answer: <neutral>", |
| "label_mapping": { |
| "entailment": "entailment", |
| "contradiction": "contradiction", |
| "neutral": "neutral" |
| } |
| } |
| }, |
| "qa-zero": { |
| "entailment": { |
| "preffix": "Are these two sentences entailed? Please, answer between <yes> or <no>.", |
| "label_mapping": { |
| "yes": "entailment", |
| "no": "not_entailment" |
| } |
| }, |
| "contradiction": { |
| "preffix": "Are these two sentences contradictions? Please, answer between <yes> or <no>.", |
| "label_mapping": { |
| "yes": "contradiction", |
| "no": "not_contradiction" |
| } |
| }, |
| "neutral": { |
| "preffix": "Are these two sentences unrelated? Please, answer between <yes> or <no>.", |
| "label_mapping": { |
| "yes": "neutral", |
| "no": "not_neutral" |
| } |
| } |
| }, |
| "qa-few": { |
| "entailment": { |
| "preffix": "Are these two sentences entailed? Please, answer between <yes> or <no>. Here you have some examples: Postal Service were to reduce delivery frequency -> The postal service could deliver less frequently: <yes>. This elegant spa town on the edge of the Lac du Bourget has offered cures for rheumatism and other ailments for centuries -> The town was only established in the past fifty years: <no>. And while we allow people to give a kidney to their child , we do not allow them to donate their heart -> You can't always donate organs to your child: <no>.", |
| "label_mapping": { |
| "yes": "entailment", |
| "no": "not_entailment" |
| } |
| }, |
| "contradiction": { |
| "preffix": "Are these two sentences contradictions? Please, answer between <yes> or <no>. Here you have some examples: Postal Service were to reduce delivery frequency -> The postal service could deliver less frequently: <no>. This elegant spa town on the edge of the Lac du Bourget has offered cures for rheumatism and other ailments for centuries -> The town was only established in the past fifty years: <yes>. And while we allow people to give a kidney to their child , we do not allow them to donate their heart -> You can't always donate organs to your child: <no>.", |
| "label_mapping": { |
| "yes": "contradiction", |
| "no": "not_contradiction" |
| } |
| }, |
| "neutral": { |
| "preffix": "Are these two sentences unrelated? Please, answer between <yes> or <no>. Here you have some examples: Postal Service were to reduce delivery frequency -> The postal service could deliver less frequently: <no>. This elegant spa town on the edge of the Lac du Bourget has offered cures for rheumatism and other ailments for centuries -> The town was only established in the past fifty years: <no>. And while we allow people to give a kidney to their child , we do not allow them to donate their heart -> You can't always donate organs to your child: <yes>.", |
| "label_mapping": { |
| "yes": "neutral", |
| "no": "not_neutral" |
| } |
| } |
| } |
| } |
| } |
