# Verbs Guide

Nouns (person, place, thing, or concept) and verbs (words that describe an action or state of being) are the hearts and souls of all sentences. And verbs in particular are among the essential building blocks of communication in any language. Apart from short interjections like "Caution!" there is no (complete) sentence without a verb: The verb controls the sentence structure and arranges the word order. The relevance of verbs for text generation appears in two main areas:

  1. As a central element of sentences it determines the other parts of the text. Therefore, to get a grammatically correct text, you need to know how verbs work and what they affect.
  2. Verbs rarely come from the data when generating text, so you have the greatest scope for designing your text at this point. You can use them to make texts lively and descriptive and thus increase the text quality.

# What to expect in this guide

  • some general grammar information (what are verbs, how are they used, rules for flexibility)
  • some information about the software (automated annotation/container suggestions)
  • some examples from different languages
  • (?) some style advises : center your statements around meaningful verbs

# Verbs - how they work in language

Verbs can take different forms depending on their grammatical function: This phenomenon is called verbal inflection. What these inflections look like depends on the individual languages. These are the most common categories for which changes can be made to the verb form: The number (singular/plural), genus (feminin/masculin/neutral/) and person of the subject. Then tense (present, past, futur etc), mood (indicative, subjunktive) and voice (active, passive).


What is the difference between verb and predicate? The verb is the core of a predicate. It must contain a verb but can have more elements, too (like object, adverb or auxiliaries)

And verbs also affect the sentence structure themselves; they are the ones that matter when it comes to the objects in the sentence. How many objects a sentence contains, or whether there is an object at all, depends on the verb, as does the case of the object (accusative, dative, genitive).

# Verbs on the NLG Platform

# Annotation to ensure grammatical correctness

Grammar has many dependencies so changes in the data can lead to required changes in the verbs. To annotate a text simply means to add some information mostly in form of meta tags. In the field of NLG the software uses this kind of additional input about the structure of a given text, such as labelling the variable parts of a text that are derived from the data or tagging grammar parts, as rule sets for generating new texts. In this way, one builds a structure for a sentence: If certain parts of the text change, for example, due to different data, all words referring to them can be adjusted correctly.

// hier noch Bild einfügen


# What does automatic annotation do?

While you previously did the annotation work yourself, the automatic annotation feature now has the ability to apply these meta tags on its own on the statements you’ve written.

The automatic annotation analyzes and tags your statement from different points of view:

  • It recognizes the variables in the written statement and links them to the according node.
  • It recognizes the grammatical structure of the statement (or the parts you’ve marked) and tags the parts of speech.
  • It identifies the words that build a unit, defines its grammatical role and annotates the grammatical cases, numbers or tense.

# Creating Verb Container

An important aspect of annotation is to group together the words that belong to a label. This is simple when determining the word types (parts of speech), since here the tag refers to a single word. The situation is different, for example, with grammatical roles, where several words can be combined.

On the NLG platform the words are grouped on a functional level and then are managed together in a unit, which is called a container. One of the important functions of container is to store the reference to the variables or other nodes on the one hand and information about the structure of a statement on the other. Verb containers, unlike the other two container types, have the sole function of grammatical regulation because verbs cannot be derived from data or nodes.

The form that the verb takes comes primarily from the subject. Depending on what properties of the subject, the verb form changes. What other factors you need to determine so that the verb is output correctly, then varies depending on the language.

:::Some examples: One box contains dandelions. Five boxes contain dandelions. Eine Schachtel enthielt Löwenzahn. Fünf Schachteln enthielten Löwenzahn. Une boîte contiendra des pissenlits. Cinq boîtes contiendront des pissenlits. В одной коробке одуванчики. В пяти коробках одуванчики.
::: /// diese Beispiele in das Projekt einbauen und nochmal auf der Plattform zeigen.

# Compound Verbs

While simple verb forms, as shown above, are formed directly on the verb itself, compound verb forms are formed by combining the verb with one or more auxiliary verbs. These auxiliary verbs help the verb, so to speak, to indicate the respective form. Compound verb forms exist, for example

  1. as tenses:
  2. in passive constructions

# The components of Verb containers

To configure a verb container you have to set in the lemma of the verb. The software can look up the lemma with the annotate feature or you can enter it yourself.

::: What does *Lemma * mean? In the NLG Cloud a lemma is the form of the verb that is used in a dictionary.

There are two ways to configure verb containers:

  1. You put all the information () into the forms
  2. You refer to the subject (the role) to get the information for inflection.

::: Tip As a thumb of rule for annotating and creating containers: You have to create a container for the case that changes are expected. This means, :

  • if you have the subject of the statement derived from a variable
  • you only have to change the part of a compound verb that is inflected. :::

# Lesson 1


How to create and configure a verb container for an english statement:

  1. Add statement (simple)
  2. Accept the suggestion.
  3. Explanation: What is a lemma? How to configure the other parts (number, )

This is simple annotation you just take that if you know that the subject does not change in number. Because number ist the only aspect of the subject changing the outcome of the verb. This is the right procedure for working with static text (no data, no variance (trough branches?)): You can change the number, person or tense in the written statement or to prompt the software to do this automatically with changing the


  1. Tippfehler bei der Überarbeitung vermeiden.
  2. Unsicherheit bei Verbformen z.B. wenn man nicht in seiner Muttersprache arbeitet.

# Lesson 2


similar to lesson 1 but in German

# Roles and copy grammar from

kurz erläutern, was wann passt usw.

Concepts: roles as references to secure the right outcome for changed elements in a statement.

# Lesson 3


How to work with roles:

  1. Add statement
  2. accept the suggestions
  3. Name the role of the subject
  4. Name the role predicate XX
  5. Click gets configuration from subject

# Using verbs for good text quality in NLG

Write with nouns and verbs, not with adjectives and adverbs.” (William , Elements of Style)

On the NLG platform, the values from the data are very prominent because they form the basis for the statements and they also can appear directly as variables in the text. Nevertheless, when writing, it is worthwhile to start designing the sentences with the verb, because this can significantly increase the quality of the texts. The more precise and appropriate the verbs are, the more clear and understandable the text will be. And in addition to this the verb is the element you have the highest level of freedom for creating in a text generation project, because it is usually not directly derived from your data, like other elements of your text.

::: Tip Use verbs as often as you can: Opting for verbs over nouns will not only make your sentences flow better but also reduce your word count because you will avoid the articles (e.g., "an," "the") and prepositions (e.g., "in," "on") required to make nouns work. :::

# Different verb categories

To be able to use the power of verbs skillfully, it is helpful to have an overview of verbs. Depending on their stylistic and grammatical function, verbs can be divided into three categories.

  1. action verbs are all verbs that show action. They make sentences vivid. These are the verbs you should use whenever possible.
  • The doctor wrote the prescription.
  • Emma buys a ticket.
  • Anna backt Plätzchen.
  • Emil überbrückt die Pause.
  1. linking verbs (state of being verbs): They connect (link) the subject to another word or words that describe or rename the subject. Linking verbs show no action but refer to states.
to be senses condition
--- --- ---
is, are, look, feel, seem, sound, taste, smell appear, become, seem

Three verbs are always linking verbs: to be, to become and to seem. There are verbs that can be linking verbs in some cases, but are action verbs in other cases. If you can substitute the verb with is it is probably a linking verb.

::: examples linking verbs

  • Tom ist ein netter Junge. Er bleibt gesund.
  • Mont Blanc bedeutet weißer Berg
  • Ich fühle mich nicht wohl.
  • I
  1. auxillary (helping) verbs always appear with another verb (the main verb) to form the “complete verb.” They indicate such things as tense, voice, mood, person, and number. A sentence can have more than one helping verb.

# How to choose the right Verbs

One rule of thumb is to choose the verb that carry specific meaning over more generic verbs. Correct weak verbs by omitting them and replacing them with a more meaningful verb. Notice that you will need to add information as you specify the nature of the action.

:::Tipp If you search your text on linking verbs or weak verbs, you will also discover other stylistic weaknesses, such as nominalization or passive voice, because they usually go hand in hand. :::

# Replace linking verbs with action verbs

no Anna is a lover of country living. yes Anna treasures country living. nein Das Smartphone ist als Kameraersatz einsetzbar. ja Das Smartphone macht exzellente Bilder. no She is of the opinion that.. yes She thinks that.

# Look for the most concise verbs

Try to find the most accurate verb this is the one that does not relay on an adverb to be precise: no The dog ran quickly through the bushes. yes The dog dashed through the bushes. nein Die Kamera-Ausrüstung

# What's next?