- Even if the turn-out to the election was within the European average, that is not very high, I have the conviction that, due to the involvement of our new colleagues in Romania, Romanian citizens will become ever more aware of the impact the European Parliament’s activity has on their day-to-day life.
- Även om valdeltagandet låg nära EU-genomsnittet, som inte är så högt, är jag övertygad om att de rumänska medborgarna, tack vare deltagandet av våra nya rumänska kolleger, i ännu högre grad kommer att bli medvetna om den inverkan som Europaparlamentets verksamhet har på deras dagliga liv.
- Madam President, the death of the dissident Orlando Zapata as a result of a hunger strike and the arrest of the blogger Yoani Sánchez, who told the world about day-to-day life in Socialist Cuba, make clear that we must continue with the link established in our Cuba policy in 1996 with progress on democratisation and human rights.
- Dissidenten Orlando Zapatas död till följd av en hungerstrejk och gripandet av bloggaren Yoani Sánchez, som berättade för världen om det dagliga livet på det socialistiska Kuba, visar tydligt att vi måste gå vidare med den förbindelse som upprättades i vår Kubapolitik 1996 med framsteg i fråga om demokratisering och mänskliga rättigheter.
show query
SET search_path TO f9miniensv;
WITH
list AS (SELECT
t11.token_id AS t11,
t12.token_id AS t12,
t21.token_id AS t21,
t22.token_id AS t22,
r1.dep_id AS dep1,
r2.dep_id AS dep2
FROM
deprel r1
JOIN depstr s1 ON s1.dep_id = r1.dep_id
JOIN word_align a1 ON a1.wsource = r1.head AND a1.wsource < a1.wtarget
JOIN word_align a2 ON a2.wsource = r1.dependent
JOIN deprel r2 ON r2.head = a1.wtarget AND r2.dependent = a2.wtarget
JOIN depstr s2 ON s2.dep_id = r2.dep_id
JOIN token t11 ON t11.token_id = r1.head
JOIN token t21 ON t21.token_id = r2.head
JOIN token t12 ON t12.token_id = r1.dependent
JOIN token t22 ON t22.token_id = r2.dependent
WHERE
s1.val = 'amod' AND
s2.val = 'AT' AND
t11.ctag = 'NOUN' AND
t21.ctag = 'NOUN' AND
t12.ctag = 'ADJ' AND
t22.ctag = 'ADJ' AND
t11.lemma_id = 41301 AND
t12.lemma_id = 53472 AND
t21.lemma_id = 40052 AND
t22.lemma_id = 40358),
stats AS (SELECT
sentence_id,
count(DISTINCT token_id) AS c,
count(*) AS c_aligned,
count(DISTINCT wtarget) AS c_target
FROM
token
LEFT JOIN word_align ON wsource = token_id
WHERE
sentence_id IN (
SELECT sentence_id
FROM
list
JOIN token ON token_id IN(t11, t21)
)
GROUP BY sentence_id),
numbered AS (SELECT row_number() OVER () AS i, *
FROM
list),
sentences AS (SELECT *, .2 * (1 / (1 + exp(max(c) OVER (PARTITION BY i) - min(c) OVER (PARTITION BY i)))) +
.8 * (1 / log(avg(c) OVER (PARTITION BY i))) AS w
FROM
(
SELECT i, 1 AS n, sentence_id, ARRAY[t11,t12] AS tokens
FROM
numbered
JOIN token ON token_id = t11
UNION SELECT i, 2 AS n, sentence_id, ARRAY[t21,t22] AS tokens
FROM
numbered
JOIN token ON token_id = t21
) x
JOIN stats USING (sentence_id)
ORDER BY i, n)
SELECT
i,
n,
w,
c,
c_aligned,
c_target,
sentence_id,
string_agg(CASE WHEN lpad THEN ' ' ELSE '' END || '<span class="token' ||
CASE WHEN ARRAY[token_id] <@ tokens THEN ' hl' ELSE '' END || '">' || val || '</span>',
'' ORDER BY token_id ASC) AS s
FROM
sentences
JOIN token USING (sentence_id)
JOIN typestr USING (type_id)
GROUP BY i, n, w, c, c_aligned, c_target, sentence_id
ORDER BY w DESC, i, n;
;