- Consequently, public expenditure will also be reduced.
- Därmed minskar även de offentliga utgifterna.
- This would make it possible to carry out insightful and systematic analyses of European public expenditure.
- Det skulle göra det möjligt att genomföra insiktsfulla och systematiska analyser av de offentliga utgifterna i EU.
- An ageing population will have a considerable impact on budgets, which will in turn increase public expenditure.
- Det ökade antalet äldre kommer att ha en betydande budgetpåverkan, vilket leder till en ökning av de offentliga utgifterna.
- I believe that Ireland should join EMU at the first available opportunity, but we should implement government policies that take into account the above inflationary increases in public expenditure, the fact that there is still under-funding for essential infrastructure and the fact that it will be difficult to sustain current growth rates while economic activity in other EU countries is weak.
- Jag anser att Irland bör gå med i EMU vid första möjliga tillfälle, men vi bör anta en regeringspolitik som beaktar ovannämnda inflationsmässiga ökningar av de offentliga utgifterna, det faktum att det fortfarande föreligger underfinansiering för nödvändig infrastruktur, och det faktum att det kommer att bli svårt att vidmakthålla den nuvarande tillväxttakten när de ekonomiska aktiviteterna i andra EU-länder är svaga.
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 = 3035 AND
t12.lemma_id = 32916 AND
t21.lemma_id = 55319 AND
t22.lemma_id = 6676),
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;
;