- A positive view can also be taken of the Integrated Administrative and Control System (IACS), which covers 56% of expenditure within the framework of the common agricultural policy.
- Vi kan också välkomna det integrerade systemet för administration och kontroll (IACS), som täcker 56 procent av utgifterna inom ramen för den gemensamma jordbrukspolitiken.
- In Article 7 of his ‘draft act’, the rapporteur has had the good sense and the courage to introduce a proposal for transnational lists covering 10 % of the total seats available in the European Parliament.
- I ”förslaget till åtgärd” i artikel 7 har föredraganden haft den goda idén och modet att införa förslaget med gränsöverskridande listor som täcker 10 procent av det totala antalet platser som skall besättas i Europaparlamentet.
- The Commission has hitherto provided a grant covering 60% of the cost of the project but ECPAT has now been notified that this support from the Enterprise DG will be withdrawn as of next year and the organisation has been recommended to apply for funding from other DGs instead.
- Kommissionen har hittills ställt upp med ett bidrag som täcker 60 procent av kostnaderna för projektet, men ECPAT har nu fått besked att detta stöd från GD Näringsliv kommer dras in från och med nästa år och organisationen rekommenderas i stället söka pengar hos andra GD.
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 = 'dobj' AND
s2.val = 'OO' AND
t11.ctag = 'VERB' AND
t21.ctag = 'VERB' AND
t12.ctag = 'NOUN' AND
t22.ctag = 'NOUN' AND
t11.lemma_id = 62175 AND
t12.lemma_id = 56453 AND
t21.lemma_id = 60829 AND
t22.lemma_id = 46371),
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;
;