{
    "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"
                }
            }
        }
    }
}