--- a
+++ b/edsnlp/conjugator.py
@@ -0,0 +1,119 @@
+from typing import Dict, List, Union
+
+import mlconjug3
+import pandas as pd
+
+
+def conjugate_verb(
+    verb: str,
+    conjugator: mlconjug3.Conjugator,
+) -> pd.DataFrame:
+    """
+    Conjugates the verb using an instance of mlconjug3,
+    and formats the results in a pandas `DataFrame`.
+
+    Parameters
+    ----------
+    verb : str
+        Verb to conjugate.
+    conjugator : mlconjug3.Conjugator
+        mlconjug3 instance for conjugating.
+
+    Returns
+    -------
+    pd.DataFrame
+        Normalized dataframe containing all conjugated forms
+        for the verb.
+    """
+
+    df = pd.DataFrame(
+        conjugator.conjugate(verb).iterate(),
+        columns=["mode", "tense", "person", "term"],
+    )
+
+    df.term = df.term.fillna(df.person)
+    df.loc[df.person == df.term, "person"] = None
+
+    df.insert(0, "verb", verb)
+
+    return df
+
+
+def conjugate(
+    verbs: Union[str, List[str]],
+    language: str = "fr",
+) -> pd.DataFrame:
+    """
+    Conjugate a list of verbs.
+
+    Parameters
+    ----------
+    verbs : Union[str, List[str]]
+        List of verbs to conjugate
+    language: str
+        Language to conjugate. Defaults to French (`fr`).
+
+    Returns
+    -------
+    pd.DataFrame
+        Dataframe containing the conjugations for the provided verbs.
+        Columns: `verb`, `mode`, `tense`, `person`, `term`
+    """
+    if isinstance(verbs, str):
+        verbs = [verbs]
+
+    conjugator = mlconjug3.Conjugator(language=language)
+
+    df = pd.concat([conjugate_verb(verb, conjugator=conjugator) for verb in verbs])
+
+    df = df.reset_index(drop=True)
+
+    return df
+
+
+def get_conjugated_verbs(
+    verbs: Union[str, List[str]],
+    matches: Union[List[Dict[str, str]], Dict[str, str]],
+    language: str = "fr",
+) -> List[str]:
+    """
+    Get a list of conjugated verbs.
+
+    Parameters
+    ----------
+    verbs : Union[str, List[str]]
+        List of verbs to conjugate.
+    matches : Union[List[Dict[str, str]], Dict[str, str]]
+        List of dictionary describing the mode/tense/persons to keep.
+    language : str, optional
+        [description], by default "fr" (French)
+
+    Returns
+    -------
+    List[str]
+        List of terms to look for.
+
+    Examples
+    --------
+    >>> get_conjugated_verbs(
+            "aimer",
+            dict(mode="Indicatif", tense="Présent", person="1p"),
+        )
+    ['aimons']
+    """
+
+    if isinstance(matches, dict):
+        matches = [matches]
+
+    terms = []
+
+    df = conjugate(
+        verbs=verbs,
+        language=language,
+    )
+
+    for match in matches:
+        q = " & ".join([f'{k} == "{v}"' for k, v in match.items()])
+        terms.extend(df.query(q).term.unique())
+
+    return list(set(terms))