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:
Pero el zurdo Neagle, que comenzó con dos triunfos brillantes a su llegada al equipo neoyorquino no pudo superar el acierto de Guillén que se convirtió en la gran estrella y lo dejó con la segunda derrota consecutiva.
Postion	Tokenization
1	Pero
2	el
3	zurdo
4	Neagle
5	,
6	que
7	comenzó
8	con
9	dos
10	triunfos
11	brillantes
12	a
13	su
14	llegada
15	al
16	equipo
17	neoyorquino
18	no
19	pudo
20	superar
21	el
22	acierto
23	de
24	Guillén
25	que
26	se
27	convirtió
28	en
29	la
30	gran
31	estrella
32	y
33	lo
34	dejó
35	con
36	la
37	segunda
38	derrota
39	consecutiva
40	.
Position	Tokenization	UPOS	Head	Deprel
1	Pero	CCONJ	20	advmod
2	el	DET	3	det
3	zurdo	NOUN	20	nsubj
4	Neagle	PROPN	3	appos
5	,	PUNCT	7	punct
6	que	PRON	7	nsubj
7	comenzó	VERB	3	acl
8	con	ADP	10	case
9	dos	NUM	10	nummod
10	triunfos	NOUN	7	obl
11	brillantes	ADJ	10	amod
12	a	ADP	14	case
13	su	DET	14	det
14	llegada	NOUN	7	obl
15	al	ADP	16	case
16	equipo	NOUN	14	nmod
17	neoyorquino	ADJ	16	amod
18	no	ADV	20	advmod
19	pudo	AUX	20	aux
20	superar	VERB	0	root
21	el	DET	22	det
22	acierto	NOUN	20	obj
23	de	ADP	24	case
24	Guillén	PROPN	22	nmod
25	que	PRON	27	nsubj
26	se	PRON	27	expl:pv
27	convirtió	VERB	24	acl
28	en	ADP	31	case
29	la	DET	31	det
30	gran	ADJ	31	amod
31	estrella	NOUN	27	obj
32	y	CCONJ	34	cc
33	lo	PRON	34	obj
34	dejó	VERB	27	conj
35	con	ADP	38	case
36	la	DET	38	det
37	segunda	ADJ	38	amod
38	derrota	NOUN	34	obl
39	consecutiva	ADJ	38	amod
40	.	PUNCT	20	punct