- It will remove barriers to the creation of new rail freight companies.
- Den kommer att undanröja hinder för bildandet av nya järnvägsfraktföretag.
- We should remove the barriers facing citizens, particularly in the new Member States, in relation to the free movement of people and services.
- Vi bör undanröja de hinder som medborgare, särskilt i de nya medlemsstaterna, ställs inför när det gäller fri rörlighet för personer och tjänster.
- It is particularly important that we continue to remove barriers affecting the mobility of workers within the Union.
- Det är särskilt viktigt att vi fortsätter att undanröja hinder för arbetstagares rörlighet inom unionen.
- Only once they have joined the EU will the Balkan countries, the infamous ’powder keg’ of Europe, where the world wars were sparked off, be able to remove the barriers to cooperation between the citizens, the business structures and the cultural and scientific experts of the various states that have appeared there in recent years.
- Det är först när länderna på västra Balkan, Europas illa beryktade ”krutdurk” där världskrigen fick sitt ursprung, gått med i EU som de kommer att kunna undanröja hindren för samarbete mellan medborgarna, företagsstrukturerna och företrädarna för kultur och forskning i de stater som har uppstått i området under senare år.
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 = 14567 AND
t12.lemma_id = 7859 AND
t21.lemma_id = 37115 AND
t22.lemma_id = 31204),
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;
;