- We know from Eurobarometer opinion polls that most people are worried about GMOs.
- Vi vet från Eurobarometer-undersökningar att de flesta människor är oroade över genetiskt modifierade organismer.
- I know from the Seychelles that they are much more interested in an Indian Ocean-wide series of agreements, rather than individual agreements.
- Jag vet från Seychellerna att de är mycket mer intresserade av en serie avtal i hela Indiska oceanen än av individuella avtal.
- I think the time has come to leave hypocrisy behind and stop constantly boxing in the Turkish people, since we knew from the start that the obstacles would be difficult to overcome.
- Jag anser att det är dags att lämna hyckleriet bakom oss och att konstant brottas med Turkiets folk, för vi visste från början att hindren skulle vara svåra att komma över.
- I rise to inform Mr Bangemann of what he surely knows from his parliamentary experience:
- Jag har anmält mig till arbetsordningen för att säga till Bangemann, att han säkert vet från sin verksamhet i parlamentet att vi i denna parlamentariska kultur ofta har tre parallella sammanträden.
- In regard to the scandal about the presence of nitrofen in grains for organic chickens, we know from information provided between May and July that not all of the Member States were informed with express speed about what had happened.
- Med hänsyn till skandalen om förekomsten av nitrofen i sädeskorn avsedda för ekologiskt uppfödda kycklingar, vet vi från de upplysningar som framkom mellan maj och juli att inte alla av medlemsstaterna omedelbart blivit informerade om vad som inträffat.
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 = 'prep' AND
t11.ctag = 'VERB' AND
t21.ctag = 'VERB' AND
t12.ctag = 'ADP' AND
t22.ctag = 'ADP' AND
t11.lemma_id = 7688 AND
t12.lemma_id = 15442 AND
t21.lemma_id = 9415 AND
t22.lemma_id = 58308),
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;
;