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:
As far as I understand, this ad will get dogs excited, but my question is: Can dogs actually see the images featured in the advert like humans?
Postion	Tokenization
1	As
2	far
3	as
4	I
5	understand
6	,
7	this
8	ad
9	will
10	get
11	dogs
12	excited
13	,
14	but
15	my
16	question
17	is
18	:
19	Can
20	dogs
21	actually
22	see
23	the
24	images
25	featured
26	in
27	the
28	advert
29	like
30	humans
31	?
Position	Tokenization	UPOS	Head	Deprel
1	As	ADV	2	advmod
2	far	ADV	10	advmod
3	as	SCONJ	5	mark
4	I	PRON	5	nsubj
5	understand	VERB	2	advcl
6	,	PUNCT	10	punct
7	this	DET	8	det
8	ad	NOUN	10	nsubj
9	will	AUX	10	aux
10	get	VERB	0	root
11	dogs	ADV	10	obj
12	excited	ADJ	10	xcomp
13	,	PUNCT	17	punct
14	but	CCONJ	17	cc
15	my	PRON	16	nmod:poss
16	question	NOUN	17	nsubj
17	is	VERB	10	conj
18	:	PUNCT	17	punct
19	Can	AUX	22	aux
20	dogs	NOUN	22	nsubj
21	actually	ADV	22	advmod
22	see	VERB	17	parataxis
23	the	DET	24	det
24	images	NOUN	22	obj
25	featured	VERB	24	acl
26	in	ADP	28	case
27	the	DET	28	det
28	advert	NOUN	25	obl
29	like	ADP	30	case
30	humans	NOUN	22	obl
31	?	PUNCT	10	punct