id stringclasses 100
values | document stringclasses 100
values | gold_summary stringlengths 76 223 | aspect_selected stringclasses 3
values | prompt_type stringclasses 2
values | objective stringclasses 2
values | prompt stringlengths 2.5k 16.7k | source_dataset stringclasses 1
value | prompt_variant_id int64 0 2 | section stringclasses 1
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|---|---|---|---|---|---|---|---|---|---|
2021.acl-long.67 | Bilingual lexicons map words in one language to their translations in another , and are typically induced by learning linear projections to align monolingual word embedding spaces . In this paper , we show it is possible to produce much higher quality lexicons with methods that combine ( 1 ) unsupervised bitext mining ... | The proposed method achieves the state-of-the-art in the bilingual lexical induction task while keeping the interpretability of their pipeline. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
2020.acl-main.75 | Humor plays an important role in human languages and it is essential to model humor when building intelligence systems . Among different forms of humor , puns perform wordplay for humorous effects by employing words with double entendre and high phonetic similarity . However , identifying and modeling puns are challeng... | Puns involve implicit semantic or phonological tricks however there is no general framework to model these two types of signals as a whole. | challenge | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Extract a short summary of the core issue... | sobamchan/aclsum | 2 | full_paper |
P10-1139 | There is a growing research interest in opinion retrieval as on-line users ' opinions are becoming more and more popular in business , social networks , etc . Practically speaking , the goal of opinion retrieval is to retrieve documents , which entail opinions or comments , relevant to a target subject specified by the... | Existing approaches to the opinion retrieval task represent documents using bag-of-words disregarding contextual information between an opinion and its corresponding text. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 0 | full_paper |
P16-1067 | This paper proposes an unsupervised approach for segmenting a multiauthor document into authorial components . The key novelty is that we utilize the sequential patterns hidden among document elements when determining their authorships . For this purpose , we adopt Hidden Markov Model ( HMM ) and construct a sequential... | Experiments with artificial and authentic scientific document datasets show that the proposed model outperforms existing methods and also be able to provide confidence scores. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
P07-1026 | Convolution tree kernel has shown promising results in semantic role classification . However , it only carries out hard matching , which may lead to over-fitting and less accurate similarity measure . To remove the constraint , this paper proposes a grammardriven convolution tree kernel for semantic role classificatio... | They propose to integrate a linguistically motivated grammar-baed convolution tree kernel into a standard tree kernel to achieve better substructure matching and tree node matching. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the method or approach the autho... | sobamchan/aclsum | 0 | full_paper |
N18-1108 | Recurrent neural networks ( RNNs ) have achieved impressive results in a variety of linguistic processing tasks , suggesting that they can induce non-trivial properties of language . We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure . We test whether RNNs trained with a ge... | The RNNs trained on an LM objective can solve long-distance agreement problems well even on nonsensical sentences consistently across languages indicating their deeper grammatical competence. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the outcomes in a sentence.
---
Docum... | sobamchan/aclsum | 1 | full_paper |
N03-1024 | We describe a syntax-based algorithm that automatically builds Finite State Automata ( word lattices ) from semantically equivalent translation sets . These FSAs are good representations of paraphrases . They can be used to extract lexical and syntactic paraphrase pairs and to generate new , unseen sentences that expre... | They propose a syntax-based algorithm that builds Finite State Automata from translation sets which are good representations of paraphrases. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
P16-1067 | This paper proposes an unsupervised approach for segmenting a multiauthor document into authorial components . The key novelty is that we utilize the sequential patterns hidden among document elements when determining their authorships . For this purpose , we adopt Hidden Markov Model ( HMM ) and construct a sequential... | There is no method for multiauthor segmentation of a document into author components which can be applied to authorship verification, plagiarism detection and author attribution. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
E06-1014 | Probabilistic Latent Semantic Analysis ( PLSA ) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis ( LSA ) . However , the parameters of a PLSA model are trained using the Expectation Maximization ( EM ) algorithm , and as a result , the trained model is d... | They propose to use Latent Semantic Analysis to initialize probabilistic latent semantic analysis models, EM algorithm is further used to refine the initial estimate. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
How do the authors address the problem? Pr... | sobamchan/aclsum | 1 | full_paper |
2020.emnlp-main.505 | News headline generation aims to produce a short sentence to attract readers to read the news . One news article often contains multiple keyphrases that are of interest to different users , which can naturally have multiple reasonable headlines . However , most existing methods focus on the single headline generation .... | They propose a multi-source transformer decoder and train it using a new large-scale keyphrase-aware news headline corpus built from a search engine. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
D18-1065 | In this paper we show that a simple beam approximation of the joint distribution between attention and output is an easy , accurate , and efficient attention mechanism for sequence to sequence learning . The method combines the advantage of sharp focus in hard attention and the implementation ease of soft attention . O... | The proposed approach outperforms soft attention models and recent hard attention and Sparsemax models on five translation tasks and also on morphological inflection tasks. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
P19-1352 | Word embedding is central to neural machine translation ( NMT ) , which has attracted intensive research interest in recent years . In NMT , the source embedding plays the role of the entrance while the target embedding acts as the terminal . These layers occupy most of the model parameters for representation learning ... | They propose a language independet method where a model shares embeddings between source and target only when words have some common characteristics. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
How do the authors address the problem? Pr... | sobamchan/aclsum | 1 | full_paper |
2020.emnlp-main.384 | Word embedding models are typically able to capture the semantics of words via the distributional hypothesis , but fail to capture the numerical properties of numbers that appear in a text . This leads to problems with numerical reasoning involving tasks such as question answering . We propose a new methodology to assi... | They propose a deterministic technique to learn numerical embeddings where cosine similarity reflects the actual distance and a regularization approach for a contextual setting. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 2 | full_paper |
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