- Firstly, the technical aspect, and here the agreement is sweet:
- För det första har vi den tekniska aspekten, och här är avtalet bra:
- Those elements with which I cannot agree are, however, the dearth of protection against wine from third countries, and the excessive focus on the technical aspects of cultivation and bottling, with less attention paid to the aspects of production.
- De punkter jag emellertid inte kan uppskatta är det dåliga skyddet gentemot viner från tredje land, den överdrivna uppmärksamhet som ägnas de tekniska aspekterna i samband med beredning och buteljering och den bristande uppmärksamhet som i stället ägnas själva produktionen.
- Now is the time to set criteria which not only deal with the technical aspects of the Schengen system, but assess the impact of organised crime and corruption, also within the assessment of existing Schengen Member States, and I would like to see Europol and Eurojust involved in those assessments.
- Nu är det dags att fastställa kriterier som inte bara rör Schengensystemets tekniska aspekter utan också bedömer effekten av organiserad brottslighet och korruption, även i samband med bedömningen av de nuvarande Schengenmedlemsstaterna, och jag skulle vilja se Europol och Eurojust involverade i dessa bedömningar.
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 = 55818 AND
t12.lemma_id = 41593 AND
t21.lemma_id = 13010 AND
t22.lemma_id = 33566),
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;
;