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:
Dada la complejidad del tumor, "el monstruo", como lo llamaba, tuvo que ser tratado con una terapia experimental en el Hospital Mount Sinai de Nueva York.
Postion	Tokenization
1	Dada
2	la
3	complejidad
4	del
5	tumor
6	,
7	"
8	el
9	monstruo
10	"
11	,
12	como
13	lo
14	llamaba
15	,
16	tuvo
17	que
18	ser
19	tratado
20	con
21	una
22	terapia
23	experimental
24	en
25	el
26	Hospital
27	Mount
28	Sinai
29	de
30	Nueva
31	York
32	.
Position	Tokenization	UPOS	Head	Deprel
1	Dada	VERB	19	advcl
2	la	DET	3	det
3	complejidad	NOUN	1	nsubj
4	del	ADP	5	case
5	tumor	NOUN	3	nmod
6	,	PUNCT	1	punct
7	"	PUNCT	9	punct
8	el	DET	9	det
9	monstruo	NOUN	19	nsubj
10	"	PUNCT	9	punct
11	,	PUNCT	14	punct
12	como	SCONJ	14	mark
13	lo	PRON	14	obj
14	llamaba	VERB	9	acl
15	,	PUNCT	14	punct
16	tuvo	VERB	0	root
17	que	SCONJ	19	cc
18	ser	AUX	19	aux
19	tratado	VERB	16	conj
20	con	ADP	22	case
21	una	DET	22	det
22	terapia	NOUN	19	obl
23	experimental	ADJ	22	amod
24	en	ADP	26	case
25	el	DET	26	det
26	Hospital	PROPN	19	obl
27	Mount	PROPN	26	flat
28	Sinai	PROPN	26	flat
29	de	ADP	30	case
30	Nueva	PROPN	26	flat
31	York	PROPN	26	flat
32	.	PUNCT	16	punct