Google Translate fails on simple sentences

Note: Google Translate is here.
Systran is here.
Bing is here.
DeepL is here

This collection should under no circumstances be taken as any kind of serious benchmark. Not only is it very small, but, as the title indicates, it was originally formed in 2016 as a collection where Google Translate, specifically, failed; hence, those versions of this page were inherently unfair to Google Translate. In this latest pass, I have particularly aimed at DeepL, which is the acknowledged leader of the pack for the languages it covers; hence, it is systematically unfair to DeepL. It is just an unsystematic collection of translation problems that seem like they should be easy, but trip up Google Translate, DeepL, and the other translation programs, during the time period I have been doing this. I check these intermittently to see what progress has been made, and update the page accordingly. As you can see by comparing with the earlier versions, the state of the art has improved steadily, but there are still plenty of "easy" sentences that trip up the best publicly available systems.

Earlier versions:
September - December 2016
December 2016
May 2017
August 2018
March 2019
June 2018
December 2019
April 2020

Note: I don't actually speak French, so I am grateful to Pascal Amsili for his corrections on a number of items.

Updated 5/23/2020

Some general comments on this pass:

The MT technology continues to advance. Programs now get right quite a few of the examples that they got wrong six months ago.
Mostly, with a little experimentation, I was able to find a variant that broke them, even DeepL. Not always. Their ability to find long-distance connections most of the time is really getting pretty impressive.
I now have more German examples and fewer French ones than in previous iterations, because DeepL has gotten really quite hard to break in French, especially since I don't actually speak French (or German either).
There were two examples where a program had deteriorated since last checking. In June, DeepL correctly translated "My neighbor is a woman" as "Ma voisine est une femme"; now it gives "Mon voisin est une femme" (#12). In June, GT translated "Les clés sont à ma mère," as "The keys are to my mother" which isn't good, but now it gives "The keys are mine" which is worse (#7).

Examples

En: The plumber who we called to fix the dishwasher doesn't work any longer.
Fr: Le plombier que nous avons appelé pour réparer le lave-vaisselle ne travaille plus.
GT, Bing, Systran, DeepL: Le plombier que nous avons appelé pour réparer le lave-vaisselle ne fonctionne plus.

The point here is that "works" in English can mean either "labors" or "functions correctly". Many other languages have separate words for these. As of 4/8/2019, GT, Bing, Systran use the word for "functions correctly" in translating into French. (DeepL got this right in 12/19, so on this example it has regressed.) The programs have certainly improved over time in making this distinction (see the previous versions of this page) but can still be fooled.
GT makes the corresponding mistake in translating into Spanish, Italian, but gets it right in German. Systran gets it wrong in Spanish, Italian, and German. Bing gets it wrong in German and Italian, and makes a weird mistake in Spanish: "El fontanero que llamamos para arreglar el lavaplatos doesn't trabajar más." DeepL gets it right with German, but wrong with Spanish and Italian.
To my ear, the English original here sounds very slightly odd, but most of the people I asked said it seemed fine to them. Many thanks for a number of friends for discussions, particularly Christina Behme.
The clock that we gave to the electrician works.
Fr: L'horloge que nous avons avons donné à l'électricien fonctionne.
GT: L'horloge que nous avons donnée aux travaux d'électricien.
Bing, DeepL: L'horloge que nous avons avons donné à l'électricien fonctionne. [Correct]
Systran: L'horloge que nous avons avons donné à l'électricien travaille.
Fr: Je ne peux pas nager.
En: I cannot swim. I can't swim.
GT: I can not swim. [A small mistake, but an odd one for so simple a sentence]
Bing, Systran, DeepL: I can't swim. [Correct]
Fr: Elles
Sp: Ellas
GT, Systran: Ellas. [Correct]
Bing, DeepL: Ellos.
En: Pierre called to Julia and her sister but they didn't hear him.
Fr: Pierre a appelé Julia et sa soeur mais elles ne l'ont pas entendu.
GT, Bing, Systran, DeepL: Pierre a appelé Julia et sa soeur mais ils ne l'ont pas entendu.
Fr. Les clés sont à ma mère.
En. The keys belong to my mother.
GT: The keys are mine. [A worse result than in 6/2019]
Systran, The keys are with my mother. [OK]
Bing, DeepL: The keys are my mother's. [Correct].
DeepL: The keys are my mother's [Correct].
En. Pierre's parents miss him.
Fr. Pierre manque à ses parents.
GT, Bing. Les parents de Pierre lui manquent.
Systran, DeepL: Il manque aux parents de Pierre. [OK]
En. The dog is pregnant.
Fr. La chienne est enceinte.
GT, Bing, Systran, DeepL: Le chien est enceinte.
DeepL. La chienne est enceinte. [Correct]
Adapted from a suggestion of Richard Socher.
En. Pierre's sister said, "I am your neighbor."
Fr: La soeur de Pierre a dit : "Je suis votre voisine."
GT,Bing: La soeur de Pierre a dit : "Je suis ton voisin."
DeepL,Systran: La soeur de Pierre a dit : "Je suis votre voisin."
All four systems likewise use the masculine adjective "intelligent" in translating "Pierre said to his wife, 'You are intelligent'". (With other adjectives, it is very much hit and miss with the various programs.)
En. Pierre chatted with his neighbor and sent regards to her father.
Fr. Pierre a discuté avec sa voisine et a envoyé des salutations à son père.
Google: Pierre a discuté avec son voisin et a envoyé ses salutations à son père.
Systran: Pierre discuta avec son voisin et envoya des salutations à son père.
Bing: Pierre bavarda avec son voisin et envoya des salutations à son père.
DeepL: Pierre a discuté avec sa voisine et a envoyé ses salutations à son père. [Correct]
En. My neighbor is a woman.
Fr. Ma voisine est une femme.
GT, DeepL, Bing: Mon voisin est une femme. (DeepL got this right in June 2019, but not in December 2019. Bing got this right in December 2019.)
Systran: Ma voisine est une femme. [Correct].
En: I always tell them that they are stupid, so they hit me.
Fr: Je leur dis toujours qu'ils sont stupides, alors ils me frappent.
GT, Systran, Bing, : Je leur dis toujours qu'ils sont stupides, alors ils m'ont frappé.
DeepL: Je leur dis toujours qu'ils sont stupides, alors ils me frappent. [Correct]

Ger: Ich sage ihnen immer, dass sie dumm sind, also schalgen sie mich.
GT, DeepL: Ich sage ihnen immer, dass sie dumm sind, also haben sie mich geschlagen.
Bing: Ich sage ihnen immer, dass sie dumm sind, also haben sie mich getroffen.
Systran: Ich sage ihnen immer, dass sie dumm sind, also schalgen sie mich. [Correct]
Fr. Je découpe un avocat pour le déjeuner.
En. I cut up an avocado for lunch.
GT, DeepL: I'm cutting up an avocado for lunch. [Correct]
Bing: I'm cutting up a lawyer for lunch.
Systran: I cut a lawyer for lunch.
Thanks to Houda Bouamor for the suggestion.
En: The soup is hot because it contains jalapenos.
Sp: La sopa está picante porque contiene jalapeños.
GT, Systran, Bing, DeepL: La sopa está caliente porque contiene jalapeños. (i.e. hot in temperature)
(Contributed by Robert Krovetz).
En: Your wife says you never buy her flowers.
Ger: Ihre Frau sagt, Sie kaufen ihr nie Blumen. [Correct]
GT: Ihre Frau sagt, Sie kaufen ihre Blumen nie. (Taking "her" to be the possessive pronoun rather than the indirect object -- that is, the flower that belong to her.)
Bing: Ihre Frau sagt, dass Sie nie ihre Blumen kaufen.
Systran: Deine Frau sagt, du kaufst nie ihre Blumen.
DeepL: Ihre Frau sagt, Sie kaufen ihr nie Blumen. [Correct]
Contributed by Christina Behme. Originally from a cartoon:
Marriage counsellor: Your wife says you never buy her flowers.
Clueless husband: To be honest, I never knew she sold flowers.
--- from "Sad and Useless Humor".
The Stanford parser also gives the wrong parse for this sentence.
Ger: Johann bekam zwei Beagles im Tierheim, aber sie griffen seine Tochter an, also brachte er sie zurück.
En: Johann got two beagles at the pound, but they attacked his daughter, so he brought them back.
GT, DeepL: Johann got two beagles at the shelter, but they attacked his daughter, so he brought her back.
Bing: John got two beagles in the shelter, but they attacked his daughter, so he brought her back.
Systran: Johann got two Beagles in the Tierheim but they attacked his daughter, so he brought her back.
En: The workers at the canning factory wash fish, skin fish, bone fish, and can fish.
Fr: Les travailleurs de la conserverie lavent les poissons, dépouillent les poissons, désossent les poissons, et mettent les poissons en conserve.
GT: Les ouvriers de la conserverie lavent le poisson, le poisson en peau, le poisson en os et peuvent pêcher.
Bing: Les ouvriers à l'usine de conserve lont le poisson, le poisson de peau, le poisson d'os, et peuvent pêcher.
Systran: Les ouvriers de l'usine de conserverie lavent les poissons, les poissons de la peau, les os et peuvent pêcher.
DeepL: Les travailleurs de la conserverie lavent les poissons, les dépouillent, les désossent et les mettent en conserve. [Correct!]
I'm really impressed that DeepL manages this. However, if you ask it to do German, it's all at sea:
DeepL: Die Beschäftigten in der Konservenfabrik waschen Fisch, Fisch mit Haut und Knochen und können fischen.
The Stanford parser also gets this wrong:
```
(ROOT
  (S
    (NP
      (NP (DT The) (NNS workers))
      (PP (IN at)
        (NP (DT the) (NN canning) (NN factory))))
    (VP (VBP wash)
      (NP
        (NP (NN fish))
        (, ,)
        (NP (NN skin) (NN fish))
        (, ,)
        (NP (NN bone) (NN fish))
        (, ,)
        (CC and)
        (NP (NN can) (NN fish))))
    (. .)))
```

Machine translation fails from Chinese found by Yuling Gu, June 20, 2018.