- I think that there is progress to be made on the risks that can be covered by insurance policies.
- Jag anser att det är möjligt att gå längre beträffande de risker som kan täckas av försäkringar.
- The question that was asked relates to insurance, because not everything is related to uninsurable public property that can be covered by the Solidarity Fund.
- Den fråga som ställdes avser försäkringar, eftersom inte allt står i samband med icke försäkringsbar offentlig egendom som kan täckas av solidaritetsfonden.
- When charges were eventually pressed against the accused, and when it was made clear that these included a charge of accepting foreign (that is, EU) funds without authorisation, the European Commission delegation in Cairo reminded the appropriate authorities that grants to civil society organisations were perfectly proper and covered by the EU-Egypt framework convention on financial and technical cooperation.
- När de anklagade slutligen åtalades och när det klargjordes att dessa åtal innefattade en punkt om att ta emot utländska medel (till exempel från EU) utan godkännande, erinrade Europeiska kommissionens delegation i Kairo de vederbörande myndigheterna om att bidrag till civila samhällsorganisationer var fullständigt i sin ordning och täcktes av ramavtalet mellan EU och Egypten om ekonomiskt och tekniskt samarbete.
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 = 'prep' AND
t11.ctag = 'VERB' AND
t21.ctag = 'VERB' AND
t12.ctag = 'ADP' AND
t22.ctag = 'ADP' AND
t11.lemma_id = 62175 AND
t12.lemma_id = 6140 AND
t21.lemma_id = 31239 AND
t22.lemma_id = 3216),
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;
;