diff --git a/tempo_embeddings/settings.py b/tempo_embeddings/settings.py
index c7741af..fc7b46a 100644
--- a/tempo_embeddings/settings.py
+++ b/tempo_embeddings/settings.py
@@ -35,9 +35,9 @@
     # Snellius:
     Path().home() / "data",
     # Yoda drive mounted on MacOS:
-    # Path(
-    #     "/Volumes/i-lab.data.uu.nl/research-semantics-of-sustainability/semantics-of-sustainability/data"
-    # ),
+    Path(
+        "/Volumes/i-lab.data.uu.nl/research-semantics-of-sustainability/semantics-of-sustainability/data"
+    ),
 ]
 """Directories in which corpora are stored; the first one found is used."""
 
@@ -47,7 +47,7 @@
     print(f"Using corpus directory: '{CORPUS_DIR}'")
 except StopIteration:
     logging.error(f"No corpus directory found in {_CORPUS_DIRS}")
-    CORPUS_DIR = None
+    CORPUS_DIR = Path(".")
 
 DEFAULT_LANGUAGE_MODEL: str = (
     "NetherlandsForensicInstitute/robbert-2022-dutch-sentence-transformers"
diff --git a/tempo_embeddings/text/passage.py b/tempo_embeddings/text/passage.py
index 879f534..dbb1ac0 100644
--- a/tempo_embeddings/text/passage.py
+++ b/tempo_embeddings/text/passage.py
@@ -5,7 +5,7 @@
 from typing import Any, Iterable, Optional
 
 from dateutil.parser import ParserError, parse
-from pydantic import BaseModel, ConfigDict, ValidationError, field_validator
+from pydantic import BaseModel, ConfigDict, field_validator
 
 from .highlighting import Highlighting
 
@@ -29,7 +29,7 @@ def parse_date(cls, value) -> datetime.datetime:
                     if not value.tzinfo:
                         value = value.replace(tzinfo=datetime.timezone.utc)
                 except ParserError as e:
-                    raise ValidationError(e)
+                    raise ValueError("Error in Metadata") from e
             return value
 
     def __init__(
@@ -43,6 +43,11 @@ def __init__(
         char2tokens: Optional[list[int]] = None,
         unique_id: str = None,
     ):
+        """
+        Initializes a Passage object.
+
+        Raises:
+            ValidationError: If the metadata is invalid."""
         # pylint: disable=too-many-arguments
         self._text = text.strip()
         self._unique_id = unique_id
@@ -423,9 +428,9 @@ def merge_until(self, passages: list["Passage"], *, length: int) -> "Passage":
             A new Passage potentially merged to increase its length.
         """
 
-        if len(self) > length * 1.5:
-            logging.warning(
-                "Very long passage (%d characters): %s", len(self), self.metadata
+        if len(self) > length * 2:
+            logging.info(
+                "Very long passage (%d >> %d): %s", len(self), length, self.metadata
             )
         elif passages and (len(self) + len(passages[0]) <= length):
             return (self + passages.pop(0)).merge_until(passages, length=length)
diff --git a/tempo_embeddings/text/segmenter.py b/tempo_embeddings/text/segmenter.py
index fc78f29..adf03eb 100644
--- a/tempo_embeddings/text/segmenter.py
+++ b/tempo_embeddings/text/segmenter.py
@@ -9,6 +9,7 @@
 import stanza
 import torch
 import wtpsplit
+from pydantic import ValidationError
 from sentence_splitter import SentenceSplitter
 
 from .. import settings
@@ -60,13 +61,18 @@ def split(self, text: str) -> Iterable[str]:
         return NotImplemented
 
     def passages(
-        self, text: str, *, metadata: Optional[dict[str, Any]] = None
+        self,
+        text: str,
+        *,
+        metadata: Optional[dict[str, Any]] = None,
+        strict: bool = False,
     ) -> Iterable[Passage]:
         """Yield passages from the text.
 
         Args:
             text: the text to split into passages.
             metadata: the metadata to attach to the passages.
+            strict: if True, raise an error on invalid metadata. Otherwise, log a warning.
         Yields:
             Passage: the passages from the text.
         """
@@ -74,7 +80,18 @@ def passages(
         for idx, sentence in enumerate(self.split(text)):
             metadata = (metadata or {}) | {"sentence_index": idx}
 
-            yield Passage(sentence, metadata)
+            try:
+                yield Passage(sentence, metadata)
+            except ValidationError as e:
+                if strict:
+                    raise e
+                else:
+                    logging.warning(
+                        "Skipping sentence %d with invalid metadata in '%s': %s",
+                        idx,
+                        metadata.get("provenance"),
+                        e,
+                    )
 
     def passages_from_dict_reader(
         self,
diff --git a/tests/unit/text/test_segmenter.py b/tests/unit/text/test_segmenter.py
index 075f687..0825d27 100644
--- a/tests/unit/text/test_segmenter.py
+++ b/tests/unit/text/test_segmenter.py
@@ -3,6 +3,7 @@
 from io import StringIO
 
 import pytest
+from pydantic import ValidationError
 
 from tempo_embeddings.text.highlighting import Highlighting
 from tempo_embeddings.text.passage import Passage
@@ -105,6 +106,37 @@ def test_passages(self, text, expected):
         passages = SentenceSplitterSegmenter("en").passages(text)
         assert list(passages) == expected
 
+    @pytest.mark.parametrize(
+        "text,metadata,strict,expected,exception",
+        [
+            ("text", {}, True, [Passage("text", metadata={"sentence_index": 0})], None),
+            (
+                "text",
+                {"date": "01-05-1889"},
+                True,
+                [Passage("text", metadata={"date": "01-05-1889", "sentence_index": 0})],
+                None,
+            ),
+            (
+                "text",
+                {"date": "01-05-1889"},
+                False,
+                [Passage("text", metadata={"date": "01-05-1889", "sentence_index": 0})],
+                None,
+            ),
+            ("text", {"date": "99-05-1889"}, True, [], pytest.raises(ValidationError)),
+            ("text", {"date": "99-05-1889"}, False, [], None),
+        ],
+    )
+    def test_passages_metadata_strict(
+        self, text, metadata, strict, expected, exception
+    ):
+        with exception or does_not_raise():
+            passages = SentenceSplitterSegmenter("en").passages(
+                text, metadata=metadata, strict=strict
+            )
+            assert list(passages) == expected
+
     @pytest.mark.parametrize(
         "_csv, length, provenance, filter_terms, expected",
         [