- We are witnessing what is a historic moment for Sudan and actually for the whole of Africa.
- Vi bevittnar ett historiskt ögonblick för Sudan och faktiskt för hela Afrika.
- Mr President of the Commission, this is indeed an historic moment for Parliament, a five-year programme following the crisis of the Commission.
- Det här är ett historiskt ögonblick för parlamentet, ett femårsprogram efter kommissionens kris.
- I also believe that both the governments and the parliaments of Poland and the UK will come to understand this fact, and that in the near future they will enable their citizens to join in this historic moment.
- Jag tror också att regeringarna och parlamenten i Polen och Storbritannien kommer att inse detta, och att de inom en nära framtid kommer att ge sina medborgare möjlighet att delta i detta historiska ögonblick.
- My question, Mr President-in-Office of the Council, is whether or not the issues that are to be addressed at the European Councils will be referred at this historic moment to the competent institution, which is the Convention chaired by Mr Giscard d’Estaing?
- Jag frågar, herr rådsordförande, om de frågor som kommer att tas upp av Europeiska rådet kommer att översändas till detta historiska ögonblick till just den behöriga institutionen, nämligen konventionen som leds av Giscard d’Estaing?
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 = 3785 AND
t12.lemma_id = 63486 AND
t21.lemma_id = 17364 AND
t22.lemma_id = 33062),
stats AS (SELECT
sentence_id,
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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;
;