- The deletion of paragraph 24 on the link between life expectancy and the retirement age is, however, a major victory for the Group of the Progressive Alliance of Socialists and Democrats in the European Parliament, who thus wished to defend the European social model, contrary to what this measure advocated.
- Strykningen av punkt 24 om kopplingen mellan förväntad livslängd och pensionsålder är dock en stor seger för gruppen Progressiva förbundet av socialdemokrater och demokrater i Europaparlamentet, som på detta sätt ville försvara den europeiska samhällsmodellen, tvärtemot vad som var syftet med denna åtgärd.
- We will invest in new sources of sustainable growth, in smart green growth, in the networks of the future from digital infrastructure to the European super grids for electricity and gas - all this to promote high levels of employment and social provision and to reinforce the European model of society, while succeeding in an increasingly competitive world.
- Vi kommer att investera i nya källor till hållbar tillväxt, i smart grön tillväxt, i framtidens nätverk - alltifrån den digitala infrastrukturen till europeiska supernät för el och gas - och allt detta gör vi för att främja sysselsättning och sociala förmåner på hög nivå och förstärka den europeiska samhällsmodellen, samtidigt som vi hävdar oss i en allt mer konkurrensfylld värld.
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 = 2482 AND
t12.lemma_id = 21311 AND
t21.lemma_id = 30048 AND
t22.lemma_id = 11582),
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;
;