[PDF] Top 20 Trainable Methods for Surface Natural Language Generation

... The first two systems, called NLG1 and NLG2, require a corpus marked only with domainspecific semantic attributes, while the last system, called NLG3, requires a corpus marked with both [r] ... See full document

... in language make the re- sponse rather rigid. Moreover, these methods usu- ally require non-trivial manual work to create tem- plates, rendering them unscalable across ...corpus-based methods have ... See full document

... our methods are easily extended to mul- tiple derivations for each single sentence, in this work we assume access to a single derivation for each sentence in our data ... See full document

... tween them, and complex communicative goals. Prior work has approach NLG from two di- rections. One strategy is over-generation and ranking, in which an intermediate structure gen- erates many candidate sentences ... See full document

... Results of the human experiment are reported in Table 4. The first line reports the results of the reference (i.e., the Wikipedia abstract) for com- parison, while the second line is the model with paired data, and the ... See full document

... at surface realization for re- ferring expression ...to surface realizations described in the literature (Reiter and Dale, 2000) rang- ing from hand-crafted template-based realizers to data-driven ... See full document

... into generation-heavy and transfer approaches for Pictograph-to-Text transla- ...the generation-heavy approach, the words conveyed by the input pictographs will be consid- ered as a bag of ...a ... See full document

... and surface realization (Koller and Petrick, ...a surface realization module which en- codes the enriched semantic representation into natural ...integrated generation, considers both sentence ... See full document

... 70 surface linguistic features as variables, our factor analysis yielded two main factors (each containing linguis- tic features grouped in positive and negative corre- lated subgroups) which we used as our ... See full document

... Recall that the adjective bigram method depended on estimating the probabilities P( ha,bi|{a,b} ) and P( hb,ai|{a,b} ). Suppose we now assume that the probability of a particular adjective appearing first in a sequence ... See full document

... Java-based surface realiser, which performs the last step in Natural Language ...Generation. Natural Language Generation is the pro- cess of transforming non-linguistic ... See full document

... crowdsourcing methods to extract large numbers of linguistic resources which can be used by NLG ...automatic methods which can be applied to any museum database in any domain to provide all of the re- ... See full document

... To measure this, we considered properties for an elevator controller, a file system and a coffee vending machine. We then built a series of scripts, starting with a basic one and progressively adding more complex ... See full document

... via natural language are in their ...automatic methods for creating natural language generation (NLG) components that can produce quality output ...tic methods for NLG may ... See full document

... 2013). We perform experiments at generating lan- guage at the word as well as character-level. The CMU−SE dataset consists of 44,016 sentences with a vocabulary of 3,122 words, while the Penn Treebank consists of 42,068 ... See full document

... one of the best-performing systems of the GIVE-1 Challenge. Baseline B, like the original “Austin” system, issues navigation instructions by precom- puting the shortest path from the IF’s current lo- cation to the ... See full document

... In the same manner, Zhong, Xiong, and Socher (2017) as- sume the availability of the query ground truth (intermediate labels) and the database response. They propose Seq2SQL, which is a modular approach to translate ... See full document

... in Natural Language Processing tasks, but provide information about the word but not about its con- ...using language models in addition to word embeddings (Peters et ...pre-trained language ... See full document

... expression generation and aggregation) at once by treating microplanning as a search ...ing generation it tries to find an utterance which is in accordance with the constraints set by its input (a grammar, ... See full document

... For example, in response to requests for definitions, the constituency schema is selected when the relevant knowledge pool contains a rich description of the questioned object's sub-clas[r] ... See full document