diff --git a/nlp-service/extractor.py b/nlp-service/extractor.py
index 7ca84f82..19543af5 100644
--- a/nlp-service/extractor.py
+++ b/nlp-service/extractor.py
@@ -86,3 +86,85 @@ def detect_person_role(doc, per_spans: list, lang: str) -> str:
             return "receiver"
 
     return "any"
+
+
+# ── Step 3: Date parsing ─────────────────────────────────────────────────────
+
+_YEAR_RE = re.compile(r"^\d{4}$")
+
+_DATE_BEFORE: dict[str, frozenset[str]] = {
+    "de": frozenset({"vor"}),
+    "en": frozenset({"before"}),
+    "es": frozenset({"antes"}),
+}
+
+_DATE_AFTER: dict[str, frozenset[str]] = {
+    "de": frozenset({"nach"}),
+    "en": frozenset({"after"}),
+    "es": frozenset({"después", "despues"}),
+}
+
+_DATE_BETWEEN: dict[str, frozenset[str]] = {
+    "de": frozenset({"zwischen"}),
+    "en": frozenset({"between"}),
+    "es": frozenset({"entre"}),
+}
+
+
+def _parse_date_text(text: str, lang: str) -> date | None:
+    text = text.strip()
+    if _YEAR_RE.match(text):
+        year = int(text)
+        if 1000 < year < 3000:
+            return date(year, 1, 1)
+    parsed = dateparser.parse(
+        text,
+        languages=[lang],
+        settings={"PREFER_DAY_OF_MONTH": "first", "RETURN_AS_TIMEZONE_AWARE": False},
+    )
+    return parsed.date() if parsed else None
+
+
+def _year_end(d: date) -> date:
+    """If d is Jan 1, return Dec 31 of the same year (year-only boundary)."""
+    if d.month == 1 and d.day == 1:
+        return date(d.year, 12, 31)
+    return d
+
+
+def extract_dates(doc, lang: str) -> tuple[str | None, str | None]:
+    """Return (date_from, date_to) as ISO strings or None."""
+    date_spans = [ent for ent in doc.ents if ent.label_ == "DATE"]
+    if not date_spans:
+        return None, None
+
+    between_tokens = _DATE_BETWEEN[lang]
+    before_tokens = _DATE_BEFORE[lang]
+    after_tokens = _DATE_AFTER[lang]
+
+    # "zwischen X und Y" / "between X and Y" — two DATE spans form a range
+    has_between = any(tok.lower_ in between_tokens for tok in doc)
+    if has_between and len(date_spans) >= 2:
+        parsed = []
+        for span in date_spans[:2]:
+            d = _parse_date_text(span.text, lang)
+            if d:
+                parsed.append(d)
+        if len(parsed) == 2:
+            parsed.sort()
+            return parsed[0].isoformat(), _year_end(parsed[1]).isoformat()
+
+    # Single DATE span — use direction token
+    span = date_spans[0]
+    d = _parse_date_text(span.text, lang)
+    if not d:
+        return None, None
+
+    prev_lower = doc[span.start - 1].lower_ if span.start > 0 else ""
+
+    if prev_lower in before_tokens:
+        return None, _year_end(d).isoformat()
+    if prev_lower in after_tokens:
+        return d.isoformat(), None
+    # Bare year/date — closed year-range
+    return d.isoformat(), _year_end(d).isoformat()
diff --git a/nlp-service/test_extractor.py b/nlp-service/test_extractor.py
index fe14d4b1..b79d188c 100644
--- a/nlp-service/test_extractor.py
+++ b/nlp-service/test_extractor.py
@@ -182,3 +182,72 @@ def test_role_receiver_to_english(nlp_en):
     doc = _make_doc_with_ents(nlp_en, "letters to Marie", [(11, 16, "PER")])
     per_spans = list(doc.ents)
     assert detect_person_role(doc, per_spans, "en") == "receiver"
+
+
+# ── Date parsing ─────────────────────────────────────────────────────────────
+
+def test_date_vor_1920(nlp_de):
+    from extractor import extract_dates
+    # "Briefe vor 1920" — "1920" at chars 11..15
+    doc = _make_doc_with_ents(nlp_de, "Briefe vor 1920", [(11, 15, "DATE")])
+    date_from, date_to = extract_dates(doc, "de")
+    assert date_from is None
+    assert date_to == "1920-12-31"
+
+
+def test_date_nach_1900(nlp_de):
+    from extractor import extract_dates
+    # "Briefe nach 1900" — "1900" at chars 12..16
+    doc = _make_doc_with_ents(nlp_de, "Briefe nach 1900", [(12, 16, "DATE")])
+    date_from, date_to = extract_dates(doc, "de")
+    assert date_from == "1900-01-01"
+    assert date_to is None
+
+
+def test_date_zwischen_1900_und_1920(nlp_de):
+    from extractor import extract_dates
+    # "zwischen 1900 und 1920"
+    # "1900" = chars 9..13, "1920" = chars 18..22
+    doc = _make_doc_with_ents(nlp_de, "zwischen 1900 und 1920", [
+        (9, 13, "DATE"),
+        (18, 22, "DATE"),
+    ])
+    date_from, date_to = extract_dates(doc, "de")
+    assert date_from == "1900-01-01"
+    assert date_to == "1920-12-31"
+
+
+def test_date_bare_year_makes_range(nlp_de):
+    from extractor import extract_dates
+    # "Briefe 1920" — no direction token → year-range
+    # "1920" = chars 7..11
+    doc = _make_doc_with_ents(nlp_de, "Briefe 1920", [(7, 11, "DATE")])
+    date_from, date_to = extract_dates(doc, "de")
+    assert date_from == "1920-01-01"
+    assert date_to == "1920-12-31"
+
+
+def test_date_no_date_entity(nlp_de):
+    from extractor import extract_dates
+    doc = _make_doc_with_ents(nlp_de, "Briefe von Opa", [])
+    date_from, date_to = extract_dates(doc, "de")
+    assert date_from is None
+    assert date_to is None
+
+
+def test_date_before_english(nlp_en):
+    from extractor import extract_dates
+    # "letters before 1920" — "1920" at chars 15..19
+    doc = _make_doc_with_ents(nlp_en, "letters before 1920", [(15, 19, "DATE")])
+    date_from, date_to = extract_dates(doc, "en")
+    assert date_from is None
+    assert date_to == "1920-12-31"
+
+
+def test_date_after_english(nlp_en):
+    from extractor import extract_dates
+    # "letters after 1900" — "1900" at chars 14..18
+    doc = _make_doc_with_ents(nlp_en, "letters after 1900", [(14, 18, "DATE")])
+    date_from, date_to = extract_dates(doc, "en")
+    assert date_from == "1900-01-01"
+    assert date_to is None