- You were informative and honest in this particular reply in terms of the date up to which you have data, in other words, up to 2007.
- Ni var informativ och ärlig när det gäller fram till vilken tidpunkt ni har uppgifter om detta, med andra ord fram till 2007.
- In the absence of clear data, it is difficult to draw any solid conclusions on their role - positive or negative - and so, before we propose legislative actions, we need to make sure that we have data so that we do not impose legislation that may be detrimental to the effective functioning of European markets.
- Innan vi föreslår en lagändring måste vi därför försäkra oss om att vi har de uppgifter som behövs, så att vi inte inför lagar som kan hindra de europeiska marknaderna från att fungera effektivt.
- It is possible that this period will be accepted and is acceptable given that a certain number of countries are reticent towards the idea of introducing a method in the immediate term and, above all, because some countries, Germany, Denmark and Finland, do not currently have the necessary data.
- Det är troligt att denna tidsperiod måste accepteras och är acceptabel, då ett antal länder är mycket betänksamma till idén att införa metoden på mycket kort sikt och framförallt för att några länder, Tyskland, Danmark och Finland, för närvarande inte har nödvändiga uppgifter.
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 = 48540 AND
t12.lemma_id = 35615 AND
t21.lemma_id = 54893 AND
t22.lemma_id = 24853),
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;
;