I'm using Freeling in my own program and it works great so far for Spanish apart from suffixes, so for words like these:

Dibújamelo.
¿Dígame?
Táchala.
Véndemelo.
Déjale.

It is returning Proper noun tag NP00000 and the word itself as the lemma.

What I don't understand is I am using the exact same code in the tutorial example and the same configuration and files as analyzer which does return the correct tags. The online demo also returns the correct tags. My code also returns no alternatives.

Snippet:

I'm working on an application which requires aligning a text (in Spanish, though I imagine this applies in general) where I need to associate the lemma with each token for a text, tokenized "naturalistically", let's say. So far I've understood how to get Freeling to produce "naturalistic" tokenization but at the cost of the rest of the analysis, at least for that token. The conllu spec obviously allows for mwt's to be represented in a way to preserve the original tokenization, but I haven't been able to find a way to get Freeling to output something like this.

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Intro
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Hi, I have been using freeling for a few months now to extract triplets. So far I have succeded in doing so by using the dependency tree and the full parse tree, but I am trying to improve my approach by using coreference, semantic graph and NERC.

I would like to remove entirely the use of "_" (underscore) from the tagging output and have each word in the group tagged separately.

Here are some examples of what I mean, along with the sections of the original text:

LaMuerte.txt:A_el_poco_rato al_poco_rato RG 1 [Al poco rato empezaron a sentirse mal]

abanderado.txt:por_medio_de por_medio_de SP 1 [le señalan las faltas del juego por medio de banderas]

abajo.txt:En_dirección_a en_dirección_a SP 1 [En dirección a la parte más baja]

Hello everyone,

I'm a computer science student and working on a project, which involves
the usage of a NLP-tool like FreeLing. My question is probably based on a
easy to see mistake I made, but I can't solve it my self. So I was hoping
someone here could help me with that.

I'm currently trying to compile example 1 on my Linux system
and get the following error:

Hello everyone.

I'm trying to replicate the dependency parsing results from the demo 4.2 on the Java 4.0 version, but I'm having some troubles doing so.

In the 4.2 demo, in the CONLL format, there are two new columns generated after selecting the dependency parsing, that's the information I'm looking for.

Hello everyone, hope you're well.

I am using the Freeling library for my Master's Degree thesis on Java, so using the JFreeling API.
Whilst it is working perfectly well on its own, I need to combine it with the ExtJWNL library to extract hyponyms and other semantic relationships.
Since introducing the JWNL library, a SIGSEGV error has been thrown at me every time:

Hello, I've been observing some inconsistencies wrt dependecy parser. I obtain different dependency parses in "dep" output level and in "semgraph" output level with Freeling 4.2 and lstm dep parser.
Frase: "atm withdrawal five hundred dollars on june seventeenth"
--outlvl dep

"dependencies" : [
{"token" : "t1.2", "function" : "ROOT", "word" :"withdrawal", "children" : [
{"token" : "t1.1", "function" : "NMOD", "word" : "atm"},


I've been using Freeling for a while and it seems like a great project. What I have used it the most for is to work with named entities. Now I am interested in adding new entities to the recognition, so I wonder if someone here has already done this and could help me a little, I have been looking at the code and it is not as simple as using a corpus labeled with the new entities, you have to change various things in the scripts.

Hello, I would like to extend the classification of named entities of Freeling, improving the ones that already exist and adding some new ones, where can I get the corpus with which the model that comes by default in Freeling was trained? the language in which I want to do this is in Spanish.