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Comment by sitkack | Hacker News Reader

HolyShit!

> The goal of Abstract Wikipedia is to let more people share in more knowledge in more languages. Abstract Wikipedia is an extension of Wikidata. In Abstract Wikipedia, people can create and maintain Wikipedia articles in a language-independent way. A Wikipedia in a language can translate this language-independent article into its language. Code does the translation.

from https://meta.wikimedia.org/wiki/Abstract_Wikipedia

Will this mean that knowledge is encoded in machine readable format and that we can start to write programs over this knowledge graph? This is huge.

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Very cool. I’m fascinated by the Wolfram Language paradigm of Knowledge Base+Programming language=Computable everything (demo: https://youtu.be/3yrVuM2SYZ8). But I could never get into the Wolfram ecosystem because it’s totally proprietary. This makes me think, does Wikidata’s model (ontologies?) provide a way to recreate the Wolfram computable everything concept as an open community project?

Yes, essentially.

Wikidata models assertions of facts about things and it has a very powerful system for writing queries to get at the facts and relationships you are interested in.

Here are some examples of what you can do with Wikidata:

https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/...

The Abstract Wikipedia idea is a great advance.

> knowledge is encoded in machine readable format and that we can start to write programs over this knowledge graph

But surely that abilty has been the goal of wikidata from the start?

Perhaps, but this seems to be moving towards a more holistic machine-readable article graph. If you look at a page from wikidata[0], it seems to be basically a key-value database (e.g. earth.highest point = [ mount everest { from sea level, 8000m } ], while the "full article" terminology used in the announcement seems like it may be even more connected/informative/structured than that.

[0]: https://www.wikidata.org/wiki/Q2

Agreed, but my point was that the aim has always been to encode these facts and then mix them into wikipedia for any assertion / attribute, so that any fact is backed by an assertion.

Exactly. The main difference is that they would now not be used to generate the infoboxes, but actual prose.

I don't see any indication that Abstract Wikipedia articles are anything more than a sequence of "constructors" and those "constructors" are essentially just triples (with qualifiers) that a "renderer" turns into a specific human language.

The example they give is the constructor:

rank(SanFrancisco, city, 4, population, California)

And the English renderer will output:

"San Francisco is the fourth largest city by population in California."

The data is stored as a bunch of triples but it encodes a graph. You can use tools like sparql to query that graph.

https://www.stardog.com/tutorials/sparql/

I'm curious whether this new project has been driven in any way by the difficulty of integrating data from Wikidata into Wikipedia. It various a lot by language, but the user communities are quite hostile to Wikidata in some cases. I think it's generally on the grounds that since Wikidata is a wiki, it can be easily vandalized and its data can't be trusted.

I dont really think so - the goal is to fill in the gaps of knowledge, not to replace existing wikipedias and whatever policies they may have.

It assumes articles will say the same thing in every language, which to me means that edit wars can now proceed on a more global basis. You're no longer fighting only the people who feel comfortable enough with your language to edit in it, you're fighting anyone who can edit the article at all around the world.

Do the Hebrew Wikipedia and the Arabic Wikipedia agree on the status of Israel?

> Do the Hebrew Wikipedia and the Arabic Wikipedia agree on the status of Israel?

If they don’t agree, perhaps they can agree to disagree and we can encode that fact instead.

A lot of serious social problems would be non-issues if only people could agree to disagree.

Unless they agree to disagree about the facts in a case where one side is factually right while the other has the consistency of a lie your 3-year-old would make up to stop you from discovering they ate all the cookies.

Agree to disagree is like saying there is no right side in this matter which is okay for topics where there isn't. Many topics however are not a matter of perspective, they are a matter of who is factually right.

IMO in such a case agreeing to disagree can often be destructive, because it legitimises a position which is factually wrong and constructs an illusion of balance where there is none.

If one side says it rains and the other says it doesn't, agreeing to disagree is wrong. If there is disagreement about what the facts mean, then sometimes both perspective can be true at the same time. This is however not as often the case as I wish it would be..

"If one side says it rains and the other says it doesn't, agreeing to disagree is wrong"

No. Agreeing to disagree is accepting, that a subject is disputed with different, even contradicting opinions.

An AI could in theory extract both versions and present them as disputed. Meaning, there are different definitions of a word and the correctness of facts.

And "raining or not" is also not as simple as you think. A person from spain will consider a certain state as raining, which a british person might see as some humidity in the air ..

Let’s take the theory of evolution for a spin. Being a theory and not a hypothesis, it is a proven scientific fact. Yet a large chunk of the population chooses to not believe it to be true. So how do we encode this knowledge?

Option 1: we call it a controversy and make it sound like because some people don’t believe in it means it might not be correct.

Option 2: we state upfront that the theory of evolution is correct but link to a “incorrect but competing viewpoint” of creationism.

Option 3: we create three articles: one about the theory of evolution, one about creationism, and one about the disagreements between the creationists and the rest of the modern world.

I like option 3 best as it is the most complete picture of the three, and all it requires is the abstract concept of controversy or disagreement. I don’t know how you encode “dumbass” in this new format but it might be a useful concept to explain to aliens if they decide to visit Earth.

>Being a theory and not a hypothesis, it is a proven scientific fact

A theory is distinct from a hypothesis, but surely it isn't itself a fact either.

Wouldn't it be better to say that the theory of evolution explains a lot of facts, which we may also call (observed) evolution? Really, aren't we just calling two related concepts "evolution"?

We use evolution every day in pharmaceuticals. We use it in our crops and in domesticated animals. If it was under question we wouldn’t call it a theory. Evolution is as real as gravity except it has even more evidence and scientific understanding, while gravity still doesn’t play nice with quantum mechanics and of course general relativity defines it as something most people cannot intuit. Evolution is a fact. I don’t see two related concepts here. Besides, consider that the second closest hypothesis that explains life on earth is that a bearded man in the sky got bored one day and created the universe, then made a man and a woman and gave them a bunch of dinosaurs to play with but instead they played with a snake, an apple, and each other’s bodies until he kicked them out of his play garden because they didn’t play by his rules, so the two of them through tremendous amounts of incest populated the earth (a fact easily disproven by a number of methods including simple genetic testing). No I don’t think it would be better to call the theory of evolution anything but a proven fact. If people want to believe in fairy tales that’s fine. But that’s not a reason to cloud scientific discovery.

I don’t know about other people, but your definition of “theory” doesn’t match mine. To me the word “theory” is almost identical to “hypothesis”, but generally a bit more comprehensive (eg consists of multiple hypothesis). Calling something a theory doesn’t require any proof nor that it be true.

There are a number of theories related to gravity. That doesn’t mean gravity isn’t a fact, it just means we don’t 100% understand how it works in all situations (eg quantum).

Similar for evolution - there are various scientific theories about the origins of species. And it is absolutely the case that we don’t know 100% how we got from Big Bang to here, thus the theories are still theories. If you just want to point to Darwinism and say fact, you’d be doing a large disservice to us all.

Gravity continued being the same thing before Newton, after Newton, and after Einstein. If we come up with a new theory of gravity, it's distinct from the phenomenon we observe. The planets are still going to go around and around, etc.

The semantic structure is the structure of the language (or the independent thing between languages). This does not automatically facilitate machine Understandable knowledge. You would need to write the code to understand it first, which is probably almost as difficult as understanding English for example.

Only when relations are defined in a kind of Prolog style in those examples it will be usable as knowledge about things other than language.

A computer might spit out texts which it guessed are connected to some question you ask it though. Does not mean it understands the relations of things.

But when can we ever really say "a machine understands" something? So perhaps there is not much of a difference?

I'm sorry if I didn't understand. Wouldn't a json or xml type data structure (where some Wikipedia stuff is already stored) would support this?

While the implications are huge, it is hard to think about what is actually being done. XML and JSON are just languages, and the type of information could be stored in any number of ways.

In my point of view, the problem here is that you could say something like "'water' and 'heat' produces 'steam'", but knowledge is never that simple, and understanding of that information is even more complicated.

I would think that Abstract Wikipedia is not the first people trying to solve such a problem, and I am very curious to see what they come up with.

EDIT: Looks like they have an example: https://meta.wikimedia.org/wiki/Abstract_Wikipedia/Examples

Isn't this the same as expert systems that led to the first AI winter?

Weren't expert systems the second AI winter? In any case, I see the end of the cold war as being the driving factor behind that winter, whatever its ordinal.

Maybe, but that doesnt mean this cant be pulled off. Neural networks were dismissed as non viable and look at them now!

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