- There is a need for measures to motivate people who become unemployed to try to find new jobs.
- Det behövs åtgärder för att motivera människor som har blivit arbetslösa att försöka hitta nya arbeten.
- We need to help people get back to work or find new jobs by making work more attractive.
- Vi måste hjälpa människor att återgå till sysselsättning eller att hitta nya arbeten genom att göra det attraktivare att arbeta.
- This fund will enable selective, individual aid to be offered to workers who have been made redundant on account of globalisation, so as to help them retrain for new jobs.
- Med hjälp av fonden kommer vi att kunna ge selektivt individuellt stöd till arbetstagare som har blivit uppsagda på grund av globaliseringen så att de kan skola om sig till nya arbeten.
- Members of the Commission must also, if requested, allow an independent ethics committee to investigate any future post up to a year after they have ceased to hold office, to ensure the new job is compatible in its nature with the work of the Commission.
- Kommissionärerna måste också i förekommande fall upp till ett år efter avslutad mandatperiod låta en oberoende etisk kommitté granska sin kommande anställning för att försäkra sig om att arbetsuppgifterna i kommissionen inte utgör något hinder för det nya arbetet.
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 = 43879 AND
t12.lemma_id = 15618 AND
t21.lemma_id = 40666 AND
t22.lemma_id = 53462),
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;
;