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They then use a generative model to rerank the translation output using additional nonworld level features.
They then use a discriminative model to rerank the translation output using additional nonworld level features.
not_entailment
2
diagnostics_test_ad4eff429b854aa59c555ec63074e5be
In contrast to standard MT tasks, we are dealing with a relatively low-resource setting where the sparseness of the target vocabulary is an issue.
Unlike in standard MT tasks, we are dealing with a relatively low-resource setting where the sparseness of the target vocabulary is an issue.
entailment
2
diagnostics_test_49b7e4abafc344d98ddbedb04d84e054
Unlike in standard MT tasks, we are dealing with a relatively low-resource setting where the sparseness of the target vocabulary is an issue.
In contrast to standard MT tasks, we are dealing with a relatively low-resource setting where the sparseness of the target vocabulary is an issue.
entailment
2
diagnostics_test_d50f288c3d30461cb9427e76d4f3b5d9
A distribution is then computed over these actions using a softmax function and particular actions are chosen accordingly during training and decoding.
Logits are then computed for these actions and particular actions are chosen according to a softmax over these logits during training and decoding.
entailment
2
diagnostics_test_259b72f6d046448294d14577e716ffa3
Logits are then computed for these actions and particular actions are chosen according to a softmax over these logits during training and decoding.
A distribution is then computed over these actions using a softmax function and particular actions are chosen accordingly during training and decoding.
entailment
2
diagnostics_test_9583fd923dac407c8dc03aa7ae194054
A distribution is then computed over these actions using a softmax function and particular actions are chosen accordingly during training and decoding.
A distribution is then computed over these actions using a maximum-entropy approach and particular actions are chosen accordingly during training and decoding.
entailment
2
diagnostics_test_381800d2b2fd41e791e519627afb4107
A distribution is then computed over these actions using a maximum-entropy approach and particular actions are chosen accordingly during training and decoding.
A distribution is then computed over these actions using a softmax function and particular actions are chosen accordingly during training and decoding.
not_entailment
2
diagnostics_test_ea2a339e20424f09b2d907202e59df21
A distribution is then computed over these actions using a softmax function and particular actions are chosen accordingly during training and decoding.
A distribution is then computed over these actions using a softmax function and particular actions are chosen randomly during training and decoding.
not_entailment
2
diagnostics_test_2f56941645e445688a99be771e19d415
A distribution is then computed over these actions using a softmax function and particular actions are chosen randomly during training and decoding.
A distribution is then computed over these actions using a softmax function and particular actions are chosen accordingly during training and decoding.
not_entailment
2
diagnostics_test_0b663c935341473b9da05256851134fb
The systems thus produced are incremental: dialogues are processed word-by-word, shown previously to be essential in supporting natural, spontaneous dialogue.
The systems thus produced support the capability to interrupt an interlocutor mid-sentence.
entailment
2
diagnostics_test_dccf31bc264d442aa5b0099acf7dc0c6
The systems thus produced support the capability to interrupt an interlocutor mid-sentence.
The systems thus produced are incremental: dialogues are processed word-by-word, shown previously to be essential in supporting natural, spontaneous dialogue.
not_entailment
2
diagnostics_test_63f04f5b1ac042839ad23d47adbd8883
The systems thus produced are incremental: dialogues are processed word-by-word, shown previously to be essential in supporting natural, spontaneous dialogue.
The systems thus produced are incremental: dialogues are processed sentence-by-sentence, shown previously to be essential in supporting natural, spontaneous dialogue.
not_entailment
2
diagnostics_test_370751adc5df40028ed0c1020254f96b
The systems thus produced are incremental: dialogues are processed sentence-by-sentence, shown previously to be essential in supporting natural, spontaneous dialogue.
The systems thus produced are incremental: dialogues are processed word-by-word, shown previously to be essential in supporting natural, spontaneous dialogue.
not_entailment
2
diagnostics_test_1a571d15528d4e2f810edd122d89517f
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, one example is enough from which to learn.
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, one-shot learning is sufficient.
entailment
2
diagnostics_test_9f6f2d1f601d4486886cb91463d2e343
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, one-shot learning is sufficient.
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, one example is enough from which to learn.
entailment
2
diagnostics_test_495654318cf5419f8fb418dfb13f6685
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, one example is enough from which to learn.
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, any number of examples is enough from which to learn.
not_entailment
2
diagnostics_test_78ca9de52b6d489e8b11774c23c6e141
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, any number of examples is enough from which to learn.
Indeed, it is often stated that for humans to learn how to perform adequately in a domain, one example is enough from which to learn.
not_entailment
2
diagnostics_test_2a0815188256409bb3816e95a30ca1f0
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end NLG.
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end natural language generation.
entailment
2
diagnostics_test_0f035a6bd06b4fb8b28d8a96dbe0078a
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end natural language generation.
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end NLG.
entailment
2
diagnostics_test_928006e8327f4c0ba74c514b8ddf2e18
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end NLG.
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end natural language parsing.
not_entailment
2
diagnostics_test_87434cd33e6c4d4f850e2b0e7da50647
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end natural language parsing.
We investigate a wide range of metrics, including state-of-the-art word-based and novel grammar-based ones, and demonstrate that they only weakly reflect human judgements of system outputs as generated by data-driven, end-to-end NLG.
not_entailment
2
diagnostics_test_b94b926aca96449788409890d6ec6664
To assess the reliability of ratings, we calculated the intra-class correlation coefficient (ICC), which measures inter-observer reliability on ordinal data for more than two raters (Landis and Koch, 1977).
To assess the unreliability of ratings, we calculated the intra-class correlation coefficient (ICC), which measures inter-observer reliability on ordinal data for more than two raters (Landis and Koch, 1977).
entailment
2
diagnostics_test_619cd347405e437f94bbc4b1aa768df3
To assess the unreliability of ratings, we calculated the intra-class correlation coefficient (ICC), which measures inter-observer reliability on ordinal data for more than two raters (Landis and Koch, 1977).
To assess the reliability of ratings, we calculated the intra-class correlation coefficient (ICC), which measures inter-observer reliability on ordinal data for more than two raters (Landis and Koch, 1977).
entailment
2
diagnostics_test_95d46c875d5c41beb47b7335aa5cd18c
We also show that metric performance is data- and system-specific.
We also show that metric performance varies between datasets and systems.
entailment
2
diagnostics_test_a0412e9b0bdc4f63960a6c0d2afc7777
We also show that metric performance varies between datasets and systems.
We also show that metric performance is data- and system-specific.
entailment
2
diagnostics_test_1f6d08a77ff84a0a84bb5a10f545d596
We also show that metric performance is data- and system-specific.
We also show that metric performance is constant between datasets and systems.
not_entailment
2
diagnostics_test_877ce74fda7d45099f8b1162d4915805
We also show that metric performance is constant between datasets and systems.
We also show that metric performance is data- and system-specific.
not_entailment
2
diagnostics_test_d17d8cbdfd5148b9993aaefbb801f747
Our experiments indicate that neural systems are quite good at producing fluent outputs and generally score well on standard word-match metrics, but perform quite poorly at content selection and at capturing long-term structure.
Our experiments indicate that neural systems are quite good at surface-level language modeling, but perform quite poorly at capturing higher level semantics and structure.
entailment
2
diagnostics_test_5f84c22c0af64237bc8f936482083490
Our experiments indicate that neural systems are quite good at surface-level language modeling, but perform quite poorly at capturing higher level semantics and structure.
Our experiments indicate that neural systems are quite good at producing fluent outputs and generally score well on standard word-match metrics, but perform quite poorly at content selection and at capturing long-term structure.
entailment
2
diagnostics_test_4619cab52be74aa5b753075c512cf8c8
Our experiments indicate that neural systems are quite good at producing fluent outputs and generally score well on standard word-match metrics, but perform quite poorly at content selection and at capturing long-term structure.
Our experiments indicate that neural systems are quite good at capturing higher level semantics and structure but perform quite poorly at surface-level language modeling.
not_entailment
2
diagnostics_test_ba4e434edc7c4ae499c4ae94156e707d
Our experiments indicate that neural systems are quite good at capturing higher level semantics and structure but perform quite poorly at surface-level language modeling.
Our experiments indicate that neural systems are quite good at producing fluent outputs and generally score well on standard word-match metrics, but perform quite poorly at content selection and at capturing long-term structure.
not_entailment
2
diagnostics_test_a99e697445ac454c9e4386d9a37b9ac1
Reconstruction-based techniques can also be applied at the document or sentence-level during training.
Reconstruction-based techniques can operate on multiple scales during training.
entailment
2
diagnostics_test_440409e3c8b7454fbb6b94f05b75e38a
Reconstruction-based techniques can operate on multiple scales during training.
Reconstruction-based techniques can also be applied at the document or sentence-level during training.
entailment
2
diagnostics_test_9a504ac31c7743deab955028dce307f0
Reconstruction-based techniques can also be applied at the document or sentence-level during training.
Reconstruction-based techniques can also be applied at the document or sentence-level during test.
not_entailment
2
diagnostics_test_19d3889e52bc4fb8998332d14777cbc2
Reconstruction-based techniques can also be applied at the document or sentence-level during test.
Reconstruction-based techniques can also be applied at the document or sentence-level during training.
not_entailment
2
diagnostics_test_5aa70f5a047940a2bc41572682fd9ca2
Reconstruction-based techniques can also be applied at the document or sentence-level during training.
Reconstruction-based techniques can only be applied at the sentence-level during training.
not_entailment
2
diagnostics_test_e176530a39494d149d7bad687cc45136
Reconstruction-based techniques can only be applied at the sentence-level during training.
Reconstruction-based techniques can also be applied at the document or sentence-level during training.
not_entailment
2
diagnostics_test_3166058d4c124976bf5640d08d6dbf54
In practice, our proposed extractive evaluation will pick up on many errors in this passage.
In practice, our proposed extractive evaluation will pick up on few errors in this passage.
not_entailment
2
diagnostics_test_742df56f4c564888960c0574f4f830cf
In practice, our proposed extractive evaluation will pick up on few errors in this passage.
In practice, our proposed extractive evaluation will pick up on many errors in this passage.
not_entailment
2
diagnostics_test_e0fed9addd47402ba261e65cffc9d400
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of passing the Bechdel test.
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of two named women characters talking about something besides men.
entailment
2
diagnostics_test_7beb12c886fe40c68d5af2fea642eafc
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of two named women characters talking about something besides men.
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of passing the Bechdel test.
entailment
2
diagnostics_test_2e083f9149df417682b835532704a2de
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of passing the Bechdel test.
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of men in the narrative talking to each other about women.
not_entailment
2
diagnostics_test_febca985e2d248efafc23374dc2e20a2
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of men in the narrative talking to each other about women.
Similarly, the use of more agent-empowering verbs in female narratives decrease the odds of passing the Bechdel test.
not_entailment
2
diagnostics_test_173e0e6bc0f2449eae7cb26fcad963b8
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of power.
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are more often in positions where they can forbid or permit actions and decisions.
entailment
2
diagnostics_test_a9a3bb4eecf343a79ef3ef7b1f9e5473
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are more often in positions where they can forbid or permit actions and decisions.
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of power.
entailment
2
diagnostics_test_725a02b78606429888afadfb9f2c95d6
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of power.
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are more often in positions where they are blocked or allowed to do things by others.
not_entailment
2
diagnostics_test_ee99f7953c63465da68b6a9bf847df72
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are more often in positions where they are blocked or allowed to do things by others.
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of power.
not_entailment
2
diagnostics_test_4b5ce4da4122409aab43fbb540d63e70
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of power.
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of low power.
not_entailment
2
diagnostics_test_5c99093f555a4b66b3d4aab6f1e68e59
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of low power.
Furthermore, male characters use inhibitory language more (inhib), which contains words pertaining to blocking or allowing, suggesting that these characters are in positions of power.
not_entailment
2
diagnostics_test_d3a4689f860048f9a2c95b96ac6e6bc7
Looking at pictures online of people trying to take photos of mirrors they want to sell is my new thing...
Looking at pictures online of people trying to take photos of mirrors is my new thing...
not_entailment
2
diagnostics_test_d4bf5b5cfa3f4fce99502c4f9fdd206c
Looking at pictures online of people trying to take photos of mirrors is my new thing...
Looking at pictures online of people trying to take photos of mirrors they want to sell is my new thing...
not_entailment
2
diagnostics_test_53877a7d37a6444bb37dbd82163bf426
A serene wind rolled across the glade.
A tempestuous wind rolled across the glade.
not_entailment
2
diagnostics_test_3eea30a0df6d47fe8943beac813ca451
A tempestuous wind rolled across the glade.
A serene wind rolled across the glade.
not_entailment
2
diagnostics_test_e8867f9ce54b4a6099a53293cc405782
A serene wind rolled across the glade.
An easterly wind rolled across the glade.
not_entailment
2
diagnostics_test_c35f7c814f0e4e82b90b9d50b189b3ec
An easterly wind rolled across the glade.
A serene wind rolled across the glade.
not_entailment
2
diagnostics_test_f53d2ff8e03a49cd96ce6e004a6e0e05
A serene wind rolled across the glade.
A calm wind rolled across the glade.
entailment
2
diagnostics_test_8b4a69255cde4d7094434995c05adc6c
A calm wind rolled across the glade.
A serene wind rolled across the glade.
entailment
2
diagnostics_test_c9f13e65eec646989a35921408fb842a
A serene wind rolled across the glade.
A wind rolled across the glade.
entailment
2
diagnostics_test_94d6627e35ce4527af476edc34597a30
A wind rolled across the glade.
A serene wind rolled across the glade.
not_entailment
2
diagnostics_test_ccfa684b4d6245a78155e43b6c2771a3
The reaction was strongly exothermic.
The reaction media got very hot.
entailment
2
diagnostics_test_a9fb8711569046b89a8da554c11760a2
The reaction media got very hot.
The reaction was strongly exothermic.
entailment
2
diagnostics_test_974c3354ce694b9ea88dc149701a4e97
The reaction was strongly exothermic.
The reaction media got very cold.
not_entailment
2
diagnostics_test_ef148c5583d84a7eb2d45d3768b2dff3
The reaction media got very cold.
The reaction was strongly exothermic.
not_entailment
2
diagnostics_test_31ce1a33a0d14ea7bdd06c4bef7fc89f
The reaction was strongly endothermic.
The reaction media got very hot.
not_entailment
2
diagnostics_test_1858480ec5eb4942a1300862b347fc17
The reaction media got very hot.
The reaction was strongly endothermic.
not_entailment
2
diagnostics_test_975dd0561b574ee3826e34449faccdc2
The reaction was strongly endothermic.
The reaction media got very cold.
entailment
2
diagnostics_test_c388dd700c4a4d7fbe981934f4ef2437
The reaction media got very cold.
The reaction was strongly endothermic.
entailment
2
diagnostics_test_5cfe702ce8c4414d8b2a00b7f14c6c55
She didn't think I had already finished it, but I had.
I had already finished it.
entailment
2
diagnostics_test_d11161fb2b0a487599b22ddd8d7ef7d5
I had already finished it.
She didn't think I had already finished it, but I had.
not_entailment
2
diagnostics_test_9b5500189324415c8667ddf6e5a6ec84
She didn't think I had already finished it, but I had.
I hadn't already finished it.
not_entailment
2
diagnostics_test_b697a50f3f1844ba871091549c0099f1
I hadn't already finished it.
She didn't think I had already finished it, but I had.
not_entailment
2
diagnostics_test_a9425041999e4b8699d3c184f3edaf4d
She thought I had already finished it, but I hadn't.
I had already finished it.
not_entailment
2
diagnostics_test_d4ae19d648304f64ac2d292bda624e77
I had already finished it.
She thought I had already finished it, but I hadn't.
not_entailment
2
diagnostics_test_405d8473c90e447aba0fc15d5001becf
She thought I had already finished it, but I hadn't.
I hadn't already finished it.
entailment
2
diagnostics_test_e79157b845b140cd91c2e9b88daa02e9
I hadn't already finished it.
She thought I had already finished it, but I hadn't.
not_entailment
2
diagnostics_test_cc1ab3215f69483bb39d6326631104d2
Temple said that the business was facing difficulties, but didn't make any specific claims.
Temple didn't make any specific claims.
entailment
2
diagnostics_test_27fa191247e24095b9ca305a55962727
Temple didn't make any specific claims.
Temple said that the business was facing difficulties, but didn't make any specific claims.
not_entailment
2
diagnostics_test_096aab491f9543c7b9edfd157338527d
Temple said that the business was facing difficulties, but didn't make any specific claims.
The business didn't make any specific claims.
not_entailment
2
diagnostics_test_8d525c72124947578a9b8f90a4096cda
The business didn't make any specific claims.
Temple said that the business was facing difficulties, but didn't make any specific claims.
not_entailment
2
diagnostics_test_b660b5f8015b42dc8cafd529b48e0d62
Temple said that the business was facing difficulties, but didn't have a chance of going into the red.
Temple didn't have a chance of going into the red.
not_entailment
2
diagnostics_test_ba06ad49d99c4aefbe312884228e841f
Temple didn't have a chance of going into the red.
Temple said that the business was facing difficulties, but didn't have a chance of going into the red.
not_entailment
2
diagnostics_test_232ad109d93e4da383cc569bdd2c0376
Temple said that the business was facing difficulties, but didn't have a chance of going into the red.
Temple said the business didn't have a chance of going into the red.
entailment
2
diagnostics_test_3cf0eefc3c834e56bc17ece3ea9b5f73
Temple said the business didn't have a chance of going into the red.
Temple said that the business was facing difficulties, but didn't have a chance of going into the red.
not_entailment
2
diagnostics_test_e33b683111f74649ad2ca2a02523af71
The profits of the businesses that focused on branding were still negative.
The businesses that focused on branding still had negative profits.
entailment
2
diagnostics_test_3c870561705247f0b18e07ac57f10915
The businesses that focused on branding still had negative profits.
The profits of the businesses that focused on branding were still negative.
entailment
2
diagnostics_test_e4f2914595184fd69f74cb68c6b4fce0
The profits of the business that was most successful were still negative.
The profits that focused on branding were still negative.
not_entailment
2
diagnostics_test_49fc38f7512f4c1ca8513be601c26904
The profits that focused on branding were still negative.
The profits of the business that was most successful were still negative.
not_entailment
2
diagnostics_test_6f80ffebecaf45419be4fd5d1d901322
The profits of the businesses that were highest this quarter were still negative.
The businesses that were highest this quarter still had negative profits.
not_entailment
2
diagnostics_test_cab989781782406b95ae39f5f4910d7f
The businesses that were highest this quarter still had negative profits.
The profits of the businesses that were highest this quarter were still negative.
not_entailment
2
diagnostics_test_f78124bca55d43ee9403da5411fd3fa3
The profits of the businesses that were highest this quarter were still negative.
For the businesses, the profits that were highest were still negative.
entailment
2
diagnostics_test_9503bd89baea42daaada38c0a3631da0
For the businesses, the profits that were highest were still negative.
The profits of the businesses that were highest this quarter were still negative.
entailment
2
diagnostics_test_ed8b2b55dfc14b51a91b451f58157854
I baked him a cake.
I baked him.
not_entailment
2
diagnostics_test_70328c2fa12a4f3da8e86cc2e7e0da6f
I baked him.
I baked him a cake.
not_entailment
2
diagnostics_test_761a860254094c2baa113fbf467fa992
I baked him a cake.
I baked a cake for him.
entailment
2
diagnostics_test_b0f52decc4b540a29683216605afcbb4
I baked a cake for him.
I baked him a cake.
entailment
2
diagnostics_test_ee499d5c33b04d00ad45f1bbf39d2c68
I gave him a note.
I gave a note to him.
entailment
2
diagnostics_test_ac9c7edf84b74238b687dae5d1dfd325
I gave a note to him.
I gave him a note.
entailment
2
diagnostics_test_162425eff44f410d85975342b1ac4cd9
Jake broke the vase.
The vase broke.
entailment
2
diagnostics_test_58b73fa230e14956af49e4a02e05ebab
The vase broke.
Jake broke the vase.
not_entailment
2
diagnostics_test_d23c9c5d72ca4c65b24f83e4626e6033
Jake broke the vase.
Jake broke.
not_entailment
2
diagnostics_test_46a43b98609e4b1b86ea87ff6998b885