- The French members of the ARE Group oppose the direction that is being taken here, as it does not seem capable of resolving the present difficulties in the rail sector.
- ARE-gruppens franska ledamöter motsätter sig denna inriktning, som inte förefaller kunna lösa de nuvarande svårigheterna inom järnvägssektorn.
- Mr President, I would like to thank all the French Members of this House most warmly and congratulate them on the French Government’s action in deporting from France the Imam of Venissieux on the grounds of his misogynistic utterances.
- Jag vill på det varmaste tacka och gratulera parlamentets alla franska ledamöter till den franska regeringens agerande med att förvisa imamen av Venissieux från Frankrike med anledning av hans kvinnoförhatliga uttalanden.
- As a French member of the Socialist Group in the European Parliament, there is an urgent need, in my view, to put an end to the inconsistencies and contradictions between the various European texts relating to information and consultation of workers, in order to prevent abuses by dishonest companies.
- Som fransk ledamot av den socialdemokratiska gruppen i Europaparlamentet anser jag att det är nödvändigt att snabbt göra slut på de inkonsekvenser och motsägelser som finns i olika EU-texter när det gäller information till och rådslag med arbetstagare i syfte att förhindra missbruk från ohederliga företags sida.
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 = 43826 AND
t12.lemma_id = 480 AND
t21.lemma_id = 36182 AND
t22.lemma_id = 58390),
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;
;