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:
She is so talented, the flowers were arranged superbly and delicately, it is so obvious to see the difference between someone fully trained and skilled compared to others.
Postion	Tokenization
1	She
2	is
3	so
4	talented
5	,
6	the
7	flowers
8	were
9	arranged
10	superbly
11	and
12	delicately
13	,
14	it
15	is
16	so
17	obvious
18	to
19	see
20	the
21	difference
22	between
23	someone
24	fully
25	trained
26	and
27	skilled
28	compared
29	to
30	others
31	.
Position	Tokenization	UPOS	Head	Deprel
1	She	PRON	4	nsubj
2	is	AUX	4	cop
3	so	ADV	4	advmod
4	talented	ADJ	0	root
5	,	PUNCT	4	punct
6	the	DET	7	det
7	flowers	NOUN	9	nsubj:pass
8	were	AUX	9	aux:pass
9	arranged	VERB	4	parataxis
10	superbly	ADV	9	advmod
11	and	CCONJ	12	cc
12	delicately	ADV	10	conj
13	,	PUNCT	4	punct
14	it	PRON	17	nsubj
15	is	AUX	17	cop
16	so	ADV	17	advmod
17	obvious	ADJ	4	parataxis
18	to	PART	19	mark
19	see	VERB	17	advcl
20	the	DET	21	det
21	difference	NOUN	19	obj
22	between	ADP	23	case
23	someone	PRON	21	nmod
24	fully	ADV	25	advmod
25	trained	ADJ	23	amod
26	and	CCONJ	27	cc
27	skilled	ADJ	25	conj
28	compared	VERB	30	case
29	to	ADP	30	case
30	others	NOUN	23	nmod
31	.	PUNCT	4	punct