As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
La secretaria de Trabajo de Izquierda Unida, Susana López, señaló que es preciso reorientar las políticas de empleo para frenar la precariedad laboral, penalizar el "abuso" de la contratación temporal y aprovechar el potencial de la economía española para crear más empleo.
Postion	Tokenization
1	La
2	secretaria
3	de
4	Trabajo
5	de
6	Izquierda
7	Unida
8	,
9	Susana
10	López
11	,
12	señaló
13	que
14	es
15	preciso
16	reorientar
17	las
18	políticas
19	de
20	empleo
21	para
22	frenar
23	la
24	precariedad
25	laboral
26	,
27	penalizar
28	el
29	"
30	abuso
31	"
32	de
33	la
34	contratación
35	temporal
36	y
37	aprovechar
38	el
39	potencial
40	de
41	la
42	economía
43	española
44	para
45	crear
46	más
47	empleo
48	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	secretaria	NOUN	12	nsubj
3	de	ADP	4	case
4	Trabajo	PROPN	2	nmod
5	de	ADP	6	case
6	Izquierda	PROPN	2	nmod
7	Unida	PROPN	6	flat
8	,	PUNCT	9	punct
9	Susana	PROPN	2	appos
10	López	PROPN	9	flat
11	,	PUNCT	9	punct
12	señaló	VERB	0	root
13	que	SCONJ	15	mark
14	es	AUX	15	cop
15	preciso	ADJ	12	ccomp
16	reorientar	VERB	15	csubj
17	las	DET	18	det
18	políticas	NOUN	16	obj
19	de	ADP	20	case
20	empleo	NOUN	18	nmod
21	para	ADP	22	mark
22	frenar	VERB	16	advcl
23	la	DET	24	det
24	precariedad	NOUN	22	obj
25	laboral	ADJ	24	amod
26	,	PUNCT	27	punct
27	penalizar	VERB	16	advcl
28	el	DET	30	det
29	"	PUNCT	30	punct
30	abuso	NOUN	27	obj
31	"	PUNCT	30	punct
32	de	ADP	34	case
33	la	DET	34	det
34	contratación	NOUN	30	nmod
35	temporal	ADJ	34	amod
36	y	CCONJ	37	cc
37	aprovechar	VERB	16	conj
38	el	DET	39	det
39	potencial	NOUN	37	obj
40	de	ADP	42	case
41	la	DET	42	det
42	economía	NOUN	39	nmod
43	española	ADJ	42	amod
44	para	ADP	45	mark
45	crear	VERB	37	advcl
46	más	ADV	47	advmod
47	empleo	NOUN	45	obj
48	.	PUNCT	12	punct