Keine Daten verfügbar. {data.get('info', '')}
"
html = HTML_CSS
analysis = data["analysis"]
# Iterate over POS categories (noun, verb, etc.)
for pos_key, entries in analysis.items():
if not entries: continue
# We usually display the best candidate, but if there are multiple distinct entries
# (like "der See" vs "die See"), the backend groups them in the list.
# We should ideally render ALL entries in the list to show the homonyms.
# This loop handles that.
for entry in entries:
# Data Extraction
inf_wikt = entry.get("inflections_wiktionary") or {}
inf_pat = entry.get("inflections_pattern") or {}
sem_comb = entry.get("semantics_combined") or {}
meta = entry.get("wiktionary_metadata") or {}
lemma = inf_wikt.get("base_form") or \
inf_pat.get("base_form") or \
sem_comb.get("lemma") or \
data.get("input_word") or "?"
# --- POS Display Logic ---
display_pos = pos_key.upper()
css_class = "pos-other"
if pos_key == 'noun':
css_class = "pos-noun"
display_pos = "SUBSTANTIV"
# Append Gender to POS badge if available
if "gender" in inf_pat:
gender_map = {"Masculine": "M", "Feminine": "F", "Neuter": "N"}
g_short = gender_map.get(inf_pat['gender'], "?")
display_pos += f" ({g_short})"
elif pos_key == 'verb':
css_class = "pos-verb"
display_pos = "VERB"
elif pos_key == 'adj' or pos_key == 'adjective':
css_class = "pos-adj"
display_pos = "ADJEKTIV"
elif pos_key == 'adv' or pos_key == 'adverb':
css_class = "pos-adv"
display_pos = "ADVERB"
# --- CARD START ---
html += f"""
" # End Header
# --- SOURCE BADGE LOGIC ---
# Determine credibility of the data
is_hybrid = inf_pat.get("is_hybrid", False)
wikt_forms_count = len(inf_wikt.get("forms_list", []))
badge_style = "float:right; font-weight:bold; font-size:0.75em; padding:2px 6px; border-radius:4px;"
if is_hybrid:
source_html = f"
Quelle: Wiktionary (Verifiziert)"
elif wikt_forms_count > 0:
source_html = f"
Quelle: Wiktionary (DB)"
elif inf_pat and "error" not in inf_pat:
source_html = f"
Quelle: Pattern (Generiert)"
else:
source_html = ""
# --- INFLECTIONS SECTION ---
html += f"
{source_html}
Morphologie & Flexion
"
html += "
"
# We render the table based on 'inf_pat' because the backend has already merged
# the Wiktionary truths into this structure.
if pos_key == 'noun':
decl = inf_pat.get('declension')
# Fallback if declension is nested in gender key
if not decl and inf_pat.get('declension_by_gender'):
# If we have a specific gender from the analysis, try to grab that specific table
target_gender = inf_pat.get("gender")
if target_gender and target_gender in inf_pat['declension_by_gender']:
decl = inf_pat['declension_by_gender'][target_gender]
else:
# Fallback: take the first available
first_gender = list(inf_pat['declension_by_gender'].keys())[0]
decl = inf_pat['declension_by_gender'][first_gender]
if decl:
# Noun Table Rows
nom_sg = decl.get('Nominativ Singular', {}).get('definite', '-')
nom_pl = decl.get('Nominativ Plural', {}).get('definite', '-')
gen_sg = decl.get('Genitiv Singular', {}).get('definite', '-')
dat_pl = decl.get('Dativ Plural', {}).get('definite', '-')
html += f"| Nom. Singular | {nom_sg} |
"
html += f"| Nom. Plural | {nom_pl} |
"
html += f"| Gen. Singular | {gen_sg} |
"
html += f"| Dat. Plural | {dat_pl} |
"
else:
html += f"| Keine Flexionsdaten verfügbar. |
"
elif pos_key == 'verb':
cj = inf_pat.get('conjugation') or {}
pres = cj.get('Präsens') or {}
past = cj.get('Präteritum') or {}
parts = inf_pat.get('participles') or {}
html += f"| Infinitiv | {inf_pat.get('infinitive', lemma)} |
"
html += f"| 3. Pers. Sg. (er/sie) | {pres.get('er/sie/es', '-')} |
"
html += f"| Präteritum (ich) | {past.get('ich', '-')} |
"
html += f"| Partizip II | {parts.get('Partizip Perfekt', '-')} |
"
html += f"| Konjunktiv II (ich) | {cj.get('Konjunktiv II', {}).get('ich', '-')} |
"
elif pos_key in ['adjective', 'adj']:
html += f"| Positiv | {inf_pat.get('predicative', lemma)} |
"
html += f"| Komparativ | {inf_pat.get('comparative', '-')} |
"
html += f"| Superlativ | {inf_pat.get('superlative', '-')} |
"
elif pos_key in ['adverb', 'adv']:
html += f"| Form | {lemma} (unveränderlich) |
"
html += "
"
# --- RAW FORMS FOOTER (The "Evidence") ---
# Display the raw forms list from DB if available, as this proves the ground truth
forms_list = inf_wikt.get("forms_list") or []
if forms_list:
# Deduplicate and flatten
unique_forms = sorted(list(set([f.get('form_text') for f in forms_list if f.get('form_text')])))
# Limit display to avoid wall of text
display_forms = ", ".join(unique_forms[:12])
if len(unique_forms) > 12: display_forms += f", ... ({len(unique_forms)-12} weitere)"
html += f"
"
html += f"Beobachtete Formen (DB): {display_forms}
"
html += "
"
# --- SEMANTICS SECTION ---
html += "
Bedeutungen & Definitionen
"
wikt_senses = sem_comb.get("wiktionary_senses") or []
ode_senses = sem_comb.get("odenet_senses") or []
if not wikt_senses and not ode_senses:
html += "
Keine Definitionen gefunden.
"
# Render Wiktionary Senses
for s in wikt_senses[:3]:
gloss_raw = s.get("definition") or ""
gloss = str(gloss_raw).replace(";", "
")
if gloss:
html += f"
Wikt {gloss}
"
# Render OdeNet Senses
for s in ode_senses[:3]:
defi = s.get("definition") or ""
if defi:
html += f"
OdeNet {defi}
"
html += "
"
# --- RELATIONS SECTION ---
rels = sem_comb.get("conceptnet_relations") or []
if rels:
html += "
Wissensgraph (Kontext)
"
top_n_rels = 6
visible_rels = rels[:top_n_rels]
hidden_rels = rels[top_n_rels:]
def render_rel(r):
rel_name = r.get("relation", "Rel")
target = r.get("other_node") or "?"
if target == "?" and "surface" in r:
parts = str(r["surface"]).split()
if len(parts) > 2: target = parts[-1]
return f"
{rel_name}: {target}"
html += "
"
for r in visible_rels:
html += render_rel(r)
html += "
"
if hidden_rels:
html += f"""
Zeige {len(hidden_rels)} weitere Relationen
"""
for r in hidden_rels:
html += render_rel(r)
html += "
"
html += "
"
html += "
Keine Tiefenanalyse verfügbar.
"
else:
html += "