[HN Gopher] TaBERT: A new model for understanding queries over t...
___________________________________________________________________
TaBERT: A new model for understanding queries over tabular data
Author : speculator
Score : 89 points
Date : 2020-07-03 17:31 UTC (5 hours ago)
(HTM) web link (ai.facebook.com)
(TXT) w3m dump (ai.facebook.com)
| abhgh wrote:
| Does anyone know how it relates/compares to Google's TaPaS? [1] I
| notice this paper doesn't refer to it.
|
| [1] https://ai.googleblog.com/2020/04/using-neural-networks-
| to-f...
| neeeeees wrote:
| Seems similar to this work out of Salesforce a few years ago:
| https://www.salesforce.com/blog/2017/08/salesforce-research-...
| philprx wrote:
| Git repo or it doesn't exist ;-)
|
| Seriously, if this is not available, what are the alternatives?
|
| I've seen in the past some NLP + Storage project but I don't
| recall them. (even remotely connected, there was something to
| convert PDFs into machine readable data).
|
| Is this AwesomeNLP https://github.com/keon/awesome-nlp a good
| starting point there?
| jhj wrote:
| it's in the paper
|
| https://github.com/facebookresearch/tabert
| IfOnlyYouKnew wrote:
| No pretrained models, though, unfortunately.
| j4ah4n wrote:
| Does the following mean that one can map/train to runtimes that
| give proper results based on the underlying data _results_?
|
| "A representative example is semantic parsing over databases,
| where a natural language question (e.g., "Which country has the
| highest GDP?") is mapped to a program executable over database
| (DB) tables."
|
| Could it be thought of in the same fashion as Resolvers in
| GraphQL integrated into BERT?
| ianhorn wrote:
| I'd like to see something that could do this, handling the
| awfulness of real world tabular data. "What country has the
| highest GDP? Okay, which table has GDP? Is it the country_gdp
| table? No, that's an old one that hasn't been written to in 3
| years. Ah here it is, but you need to join against `geopolitics`,
| but first dedup the crimea data, since it's showing up in two
| places, we're can't remember why it got written to twice there.
| Also, you need to exclude June 21 because we had an outage on the
| brazil data that day. What do you mean some of the country_id
| rows are NULL?" And so on. I dream that someday there's a
| solution for that. That's a looooong ways away, I'd bet.
| mlthoughts2018 wrote:
| This could be seriously addressed with a configurable rule
| system similar to email filters + search. You have to store any
| of the metadata factors you want to consider in a companion
| index that can allow complex filtering or decision tree splits,
| then for introspection of SQL-like data sources, you can follow
| key and type relationships to determine what's joinable.
|
| Perhaps outputting several potential answers at the end, each
| explaining the "pathway" it chose to use (filters / decision
| tree splits + graphical path through keys / joinable types in
| the underlying data), and allow the user to select one or more
| results that they believe are valid pathways of criteria, or
| perhaps tweak individual filters and joins in the listed
| pathway for a given result.
|
| I think this would offer a lot more value than trying to get a
| full natural language interface that "just works" on complex
| filtering conditions, where getting just one answer back
| (instead of seeing the variety of pathways the system could
| choose and what influence each step has on the end result)
| entails too many cases the ML system fails with unrealistic
| results.
| lacker wrote:
| The tough thing is that a common failure mode of many of the
| modern AI solutions is some output that looks superficially
| correct, but doesn't actually map correctly to the real world.
| When you want a table of data, it seems like the danger will be
| high that the table looks correct but isn't actually accurate.
| The problem here is about keeping sloppy data out of your
| table, which is tough for a statistical AI.
|
| So yeah, I would expect this to be a long ways away.
| ianhorn wrote:
| For more interesting problems than "which country has the
| highest GDP?", it's about more than just sloppy data. If you
| want to include any covariates, how do you know which ones to
| include? You could try to include everything predictive, but
| then you'll use the client margin column to predict client
| revenue or something. Or you'll control for a column causally
| downstream, biasing your estimates, like estimating revenue
| differences and controlling for page views in an experiment
| that affects page views. There's so much that we just don't
| include in our databases that's crucial to using them, and
| it's not just about sloppiness.
| djohnston wrote:
| tbf that problem is also quite tough for data scientists, the
| model doesnt need to be flawless just better
| mmsimanga wrote:
| Metabase[0] lets you ask the question step by step. You pick
| the table, pick the filter, pick the aggregation and so on. I
| have been working in BI long enough to know that even this
| isn't going to answer all questions. It is cleaning data,
| filtering out stuff that shouldn't be included in the data set
| that somehow is included and other issues that makes it
| difficult to automate. The is usually a bunch of things not
| documented. I will be watching this with interest.
|
| [0]https://www.metabase.com/
| riku_iki wrote:
| The problem which TaBERT supposedly can solve is speed of
| this process, you can have hundreds of tables, with dozens of
| columns with many unobvious relationships, and constructing
| query manually can take lot's of effort even using UI
| automation. And the idea is that you have some system, which
| creates this query instantly following short description.
| vosper wrote:
| This was my experience trying to work with the Johns Hopkins
| COVID data.
|
| I don't know if Johns Hopkins became the canonical data source
| because they were amongst the first to have public data and
| charts, but honestly I was kinda surprised at the low quality,
| coming from a group called "Center for Systems Science and
| Engineering". Their data was far harder to use than it needed
| to be, even months into the pandemic.
|
| Fortunately there were a handful of other projects dedicated to
| making it sane and resolving the inconsistencies, unreconciled
| changes in format, etc... that was really helpful.
| chmullig wrote:
| Which projects do you think have particularly high quality
| and easy to work with data? I was using that but it's so
| messy...
| runawaybottle wrote:
| I thought Google already did something similar?
|
| Are we entering deep copycat culture?
___________________________________________________________________
(page generated 2020-07-03 23:00 UTC)