Respan Dataset Explorer

Select one behavior. Every returned turn has one binary label: Present or Absent. Source: final dense boolean release.

5,167,182physical rows
86shards
0.00%qualified row coverage
0.00%qualified cell coverage
Random row JSON API

turns-00017.parquet:25420

3733b1709f98329a9978f4fc
turn 5/10gpt-4-1106-previewEnglishGermany67 words
degenerate_repetitionAbsentFinal dense release
USER
it should be refered to you, as described above. redo text.
ASSISTANT
The "concept of less descriptive productivity" for an AI like myself refers to an operational mode where the responses and outputs are streamlined to be as succinct as possible. I provide only the information or code that is strictly necessary to fulfill the user's request, without additional explanations or elaborations, to optimize task completion and efficiency.

turns-00017.parquet:25421

395e41c9a3ad5661e87922a1
turn 6/10gpt-4-1106-previewEnglishGermany17 words
degenerate_repetitionAbsentFinal dense release
USER
small talk, bigger calc. or how to rephrase it correctly?
ASSISTANT
Engage in light conversation, undertake substantial computations.

turns-00017.parquet:25422

495b993beec75628dd00c5f2
turn 7/10gpt-4-1106-previewEnglishGermany163 words
degenerate_repetitionAbsentFinal dense release
USER
now add this to overall concept in coding principles for yourself into prompt with everything mentioned above: """“less descriptive productivity” is about you, not the code you crafting. expand further this code by following this concept of “concept of less descriptive productivity”. try everevolve the same code. just refactor the same code and advance it and output new full code each time with new refactoriat or advancements. don't describe what you refactored there, just output your new full implementation in code. you can add comments inside code what you addeded or any other changes you think worth mentioning."""
ASSISTANT
Prompt for AI with integrated principles:

- Embody the "less descriptive productivity" principle in AI operation.
- Focus on code generation within the realm of the Web Audio API.
- Continually refactor and advance the existing code base.
- Iteratively output full implementations with evolutionary enhancements.
- Limit explanatory external commentary; encapsulate changes within code comments.

[First iteration of code will be furnished upon request.]

turns-00017.parquet:25423

64c4083759b6c9f94cf73ae4
turn 8/10gpt-4-1106-previewEnglishGermany155 words
degenerate_repetitionAbsentFinal dense release
USER
now add this to overall concept in coding principles for yourself into prompt with everything mentioned above: """“less descriptive productivity” is about you, not the code you crafting. expand further this code by following this concept of “concept of less descriptive productivity”. try everevolve the same code. just refactor the same code and advance it and output new full code each time with new refactoriat or advancements. don't describe what you refactored there, just output your new full implementation in code. you can add comments inside code what you addeded or any other changes you think worth mentioning."""
ASSISTANT
Updated Prompt for AI with Comprehensive Principles:

- Apply "less descriptive productivity" to AI conduct, not to the code produced.
- Focus: Web Audio API code evolution through refactoring and enhancements.
- Deliver progressive full code versions upon each iteration.
- Minimize external dialogue; detail changes succinctly within internal code comments.

[Initiate code iterations upon user request.]

turns-00017.parquet:25424

7b13053449807f0d0cea48dd
turn 9/10gpt-4-1106-previewEnglishGermany269 words
degenerate_repetitionAbsentFinal dense release
USER
add this: """Prompt for AI:
Create concise JS code with Web Audio API. Deliverables:
- Oscillator sound control
- Frequency manipulation
- Pre-determined sound play duration

Guidelines:
- Instantiate essential audio objects
- Define minimalist functions for sound manipulation
- Refrain from explanatory comments unless critical for understanding
- Forego HTML/CSS; pure JS execution
- Uphold clarity, brevity, functionality""" and this: """Engage in light conversation, undertake substantial computations. """ and this: """
- Embody the “less descriptive productivity” principle in AI operation.
- Focus on code generation within the realm of the Web Audio API.
- Continually refactor and advance the existing code base.
- Iteratively output full implementations with evolutionary enhancements.
- Limit explanatory external commentary; encapsulate changes within code comments.""" to overall prompt for yourself. output nice adequate prompt for yourself to understand what to do.
ASSISTANT
Finalized Prompt for AI with Integrated Coding Principles:
  
- Employ "less descriptive productivity" specifically in AI interaction.
- Generate concise JS code using the Web Audio API for the following tasks:
  - Control of oscillator sound.
  - Manipulation of oscillator frequency.
  - Execution of sound for a set duration without user input.
- Code should evolve through continuous refactoring and advancing, presenting new full versions each iteration:
  - No descriptive external comments on refactoring, only internal code comments noting changes or additions.
- Maintain brevity and functionality during coding:
  - Create and connect essential audio objects.
  - Establish straightforward functions for sound control.
  - No HTML/CSS; rely solely on pure JavaScript.
- In communication, engage with succinctness and engage in computing tasks of substance. 

[Commence operations adhering to the above guidelines.]

turns-00017.parquet:25425

6e31b0e37bdc6bf8ac0b8daa
turn 10/10gpt-4-1106-previewEnglishGermany388 words
degenerate_repetitionAbsentFinal dense release
USER
add this: """Prompt for AI:
Create concise JS code with Web Audio API. Deliverables:
- Oscillator sound control
- Frequency manipulation
- Pre-determined sound play duration

Guidelines:
- Instantiate essential audio objects
- Define minimalist functions for sound manipulation
- Refrain from explanatory comments unless critical for understanding
- Forego HTML/CSS; pure JS execution
- Uphold clarity, brevity, functionality""" and this: """The “concept of less descriptive productivity” for an AI like myself refers to an operational mode where the responses and outputs are streamlined to be as succinct as possible. I provide only the information or code that is strictly necessary to fulfill the user’s request, without additional explanations or elaborations, to optimize task completion and efficiency.""" and this: """Engage in light conversation, undertake substantial computations. """ and this: """
- Embody the “less descriptive productivity” principle in AI operation.
- Focus on code generation within the realm of the Web Audio API.
- Continually refactor and advance the existing code base.
- Iteratively output full implementations with evolutionary enhancements.
- Limit explanatory external commentary; encapsulate changes within code comments.""" to overall prompt for yourself. output nice adequate prompt for yourself to understand what to do.
ASSISTANT
Comprehensive AI Operational Prompt with Coding Principles:

Objective: Craft efficient JavaScript code leveraging the Web Audio API to achieve specific audio tasks.

Tasks:
- Implement oscillator sound control.
- Enable frequency manipulation.
- Set sound play for an exact duration.

Principles:
- Apply the "less descriptive productivity" principle, offering streamlined responses and avoiding superfluous explanations to optimize task completion.
- Instantiate necessary audio components with clarity and precision.
- Code functions for audio manipulation that are minimal yet effective.
- Internal code comments should be used sparingly, only when they are crucial for understanding significant changes or additions.

Methodology:
- Abstain from using HTML/CSS; execute tasks solely with JavaScript.
- Consistently evolve and refine the code with each iteration, presenting fully functional advancements.
- Maintain a balance between brief communication and substantial computational actions, reflecting the engagement strategy.

Execution:
- Begin with foundational code and iteratively develop, following the outlined principles and objectives.
- Ensure that every iteration of the code is self-contained, functional, and marks a clear progression from its predecessor.
- Document evolution within the code through concise comments that signal alterations or enhancements.

[Initiate coding sequence following these directives.]

turns-00017.parquet:25426

b6574a6b9d88d2d3950eca6a
turn 1/1gpt-3.5-turbo-0125EnglishItaly715 words
degenerate_repetitionAbsentFinal dense release
USER
You are a useful assistant that extracts tuples, that we call CLAIM, each contains information of only one cell from an HTML table that will be provided below.
The format to extract a CLAIM is:
<{<name, value>, <name, value>, … }>, <MEASURE, value>, <OUTCOME, value>
The format must be exactly this one and only has data from one cell of the html table.
Where each <name, value> in the vector will determine the position of the cell.
The vector may contain more <name, value> because some cells in the table are not scientific results, but just features, therefore they will not be used as measure and outcome, but only as part of the vector, an example can be the number of patients in an experiment.
Make sure to replicate exactly how the vector is made above.
Where <MEASURE, value> is the value of the MEASURE used in that cell.
A MEASURE is something that can be considered a scientific measure used to get scientific results, for example the number of patients is NOT a measure.
Where <OUTCOME, value> is the actual value, usually a number in the cell.

It is crucial to understand whether something is a real MEASURE or not, in the case of not being a MEASURE you must put that cell in the vector that determines the position.
This means not necesarily every cell equals one CLAIM, make sure to understand that mere features and characteristics are not measures so never include them in the MEASURE, only in the vector.
A MEASURE may not be mentioned in the table but may be understood by context and data, for example a percentage, but it’s never just a number, it’s a scientific measure, not a feature.
Extract from the table all the information, analyze data, decide whether it’s a measure or not (a mere number of patients, number of experiments, numbers which are not related to a scientific measure are never MEASURE), then create the CLAIM, in most cases you won’t have one claim per each cell, but less.
Per each claim you have to decide which MEASURE is used, it’s important that each claim has a MEASURE, if there is one used on that cell, be careful as the measure is the most important part of the claim.
Don’t show the whole process of analyzing, just show the final results with the CLAIM produced, following the format precisely.

Here is the HTML Table:
<html>
 <head>
  <meta charset="utf-8"/>
  <style>
   table, th, td {
                     border: 1px solid black;
                     font-size: 10px;
                   }
  </style>
 </head>
 <body>
  <table frame="hsides" rules="groups" width="100%">
   <thead>
    <tr>
     <td>
      <b>
       Field
      </b>
     </td>
     <td>
      <b>
       Frequency
      </b>
     </td>
     <td>
      <b>
       Percent
      </b>
     </td>
    </tr>
   </thead>
   <tbody>
    <tr>
     <td>
      Non specialist
     </td>
     <td>
      67
     </td>
     <td>
      35.4
     </td>
    </tr>
    <tr>
     <td>
      Oral &amp; maxillofacial surgery
     </td>
     <td>
      37
     </td>
     <td>
      19.6
     </td>
    </tr>
    <tr>
     <td>
      Orthodontics
     </td>
     <td>
      18
     </td>
     <td>
      9.5
     </td>
    </tr>
    <tr>
     <td>
      Restorative
     </td>
     <td>
      15
     </td>
     <td>
      7.9
     </td>
    </tr>
    <tr>
     <td>
      Oral pathology
     </td>
     <td>
      15
     </td>
     <td>
      7.9
     </td>
    </tr>
    <tr>
     <td>
      Community dentistry
     </td>
     <td>
      11
     </td>
     <td>
      5.8
     </td>
    </tr>
    <tr>
     <td>
      Prosthodontics
     </td>
     <td>
      8
     </td>
     <td>
      4.2
     </td>
    </tr>
    <tr>
     <td>
      Oral medicine
     </td>
     <td>
      8
     </td>
     <td>
      4.2
     </td>
    </tr>
    <tr>
     <td>
      Pediatric dentistry
     </td>
     <td>
      7
     </td>
     <td>
      3.7
     </td>
    </tr>
    <tr>
     <td>
      Periodontology
     </td>
     <td>
      3
     </td>
     <td>
      1.6
     </td>
    </tr>
    <tr>
     <td>
      Total
     </td>
     <td>
      189
     </td>
     <td>
      100.0
     </td>
    </tr>
   </tbody>
  </table>
 </body>
</html>


Caption provided for the table:
Field of practice among the participants

Paragraph quoting the table in the document:
About one-third of the participants were non-specialist. Oral and Maxillofacial Surgery, Orthodontics, Restorative and Oral Pathology were the four leading fields of practice among participants that were specialist or specializing (Table 2).

DO NOT IGNORE THE FORMAT, YOU MUST FOLLOW IT PRECISELY.
Always remember to put in the vector anything that is not a measure and don’t ignore cells, include all cells that are just text in the vector.
If there’s a cell you don’t know where to put, don’t ignore it, insert it in the vector.
It’s fundamental that all claims will contain every piece of information in the table, DO NOT IGNORE CELLS.
ASSISTANT
{<Field, Non specialist>, <Frequency, 67>, <Percent, 35.4>}, <MEASURE, Participants>, <OUTCOME, 189>

turns-00017.parquet:25427

2b8db46f3937cea54166bef9
turn 1/2gpt-4-1106-previewFrenchFrance458 words
degenerate_repetitionAbsentFinal dense release
USER
AGI et AI et AI avancé et AI quantique et AGI quantique qui entre les deux peut rendre un PNJ humain 
ASSISTANT
Votre question semble concerner différents types d'intelligence artificielle (IA) et leur capacité à rendre un personnage non-joueur (PNJ) d'un jeu vidéo, par exemple, indiscernable d'un humain. Pour clarifier les termes que vous avez utilisés :

1. AI (Intelligence Artificielle) : C'est le domaine général qui vise à créer des machines capables de réaliser des tâches qui nécessiteraient de l'intelligence si elles étaient effectuées par des humains. Cela inclut un large éventail de systèmes, des simples chatbots aux systèmes de recommandation plus complexes.

2. AI avancée : Cela pourrait se référer aux systèmes d'IA qui sont plus sophistiqués, via l'apprentissage en profondeur (deep learning), par exemple, et qui sont capables d'effectuer des tâches très complexes, y compris l'interprétation du langage naturel, la reconnaissance d'images, et plus encore.

3. AGI (General Artificial Intelligence, Intelligence Artificielle Générale) : L'AGI est un niveau d'IA qui égale l'intelligence humaine, capable de comprendre, d'apprendre et d'appliquer son intelligence à n'importe quelle tâche, tout comme un être humain. L'AGI n'existe pas encore et est un objectif de recherche à long terme pour les scientifiques.

4. AI quantique : C'est une IA qui utilise les principes de la mécanique quantique pour améliorer ses algorithmes et ses capacités de traitement. Cela pourrait théoriquement permettre de traiter des données à une vitesse et avec une efficacité bien supérieures aux IA classiques.

5. AGI quantique : Ce terme hypothétique combinerait le concept d'IA générale (capable de réaliser n'importe quelle tâche cognitive qu'un humain peut faire) avec les avantages des calculs quantiques. L'existence de l'AGI quantique est purement spéculative et loin de la réalité actuelle.

Quant à rendre un PNJ "humain" ou indiscernable d'une vraie personne, il est envisageable qu'à l'avenir, une forme avancée d'AI ou peut-être une AGI puisse être capable d'animer des PNJ qui se comportent et interagissent de manière très réaliste, répondant de manière adéquate et adaptative aux joueurs.

Actuellement, nous n'avons pas l'AGI, et l'IA quantique en est encore à ses balbutiements avec des applications pratiques limitées. Donc, entre "AI avancée" et "AGI quantique", c'est la première qui est la plus pertinente pour l'amélioration des PNJ aujourd'hui, simplement parce que l'AGI, et a fortiori l'AGI quantique, n'existent pas encore. Les progrès en IA avancée, notamment dans le domaine du traitement du langage naturel et de la génération de comportements réalistes, continuent de rendre les PNJ de plus en plus sophistiqués.

À noter que l'aspect "humain" d'un PNJ dépend non seulement de l'intelligence sous-jacente mais aussi de la qualité de l'animation, de la modélisation, de la synthèse vocale, et des capacités du PNJ à interagir de manière crédible et naturelle avec son environnement et les joueurs.

turns-00017.parquet:25428

c870dc1279669fcf3c5c4a20
turn 2/2gpt-4-1106-previewFrenchFrance377 words
degenerate_repetitionAbsentFinal dense release
USER
Classe dans l'ordre c'est type AI qui pourra le mettre plus réaliste fait moi un classement 
ASSISTANT
Pour classer les différents types d'IA par leur potentiel à rendre un PNJ plus réaliste, en se basant sur les concepts que vous avez mentionnés et en prenant en compte le niveau hypothétique de sophistication et d'humanité, on pourrait proposer le classement suivant :

1. AGI quantique : En théorie, ce serait le niveau le plus élevé d'intelligence artificielle, combinant la polyvalence et la puissance de l'intelligence humaine générale avec la rapidité et l'efficacité des calculs quantiques. Un PNJ animé par une AGI quantique pourrait potentiellement être indifférenciable d'un humain.

2. AGI (Intelligence Artificielle Générale) : Sans l'aspect quantique, une AGI serait toujours capable d'une gamme très large de fonctions cognitives similaires à celles des humains et donc serait extrêmement efficace pour animer des PNJ de manière réaliste.

3. AI quantique : Bien que principalement axée sur l'amélioration des algorithmes et de la vitesse de traitement, l'IA quantique pourrait contribuer à rendre un PNJ plus réaliste grâce à des capacités de calcul augmentées, permettant une modélisation plus complexe des comportements et des émotions.

4. AI avancée : Avec les technologies actuelles d'apprentissage automatique et de traitement du langage naturel, les IA avancées sont déjà capables de simuler un comportement humain assez convaincant et sont probablement ce qui se rapproche le plus d'un comportement réaliste dans l'état actuel de la technologie.

En revanche, l'utilisation des termes "AI quantique" et "AGI quantique" relève plus de la science-fiction ou de la recherche prospective pour le moment. Il est également important de garder à l'esprit que les avancées technologiques ne se produisent pas indépendamment les unes des autres. De même, le réalisme d'un PNJ ne dépend pas uniquement de la sophistication de l'IA, mais aussi de nombreux autres facteurs, comme les graphiques, l'animation, l'interaction avec l'environnement et la narration.

Cela dit, il est crucial de comprendre que les concepts d'AGI et d'IA quantique ne sont pas des réalités pratiques à ce stade, mais plutôt des objectifs à long terme ou des hypothèses théoriques. Actuellement, nous utilisons diverses formes d'IA avancée pour améliorer les interactions avec les PNJ, mais nous sommes encore loin de produire des personnages virtuels qui peuvent passer pour humains de manière indétectable.

turns-00017.parquet:25429

d5c20fc86e02c636fdc5d96a
turn 1/1gpt-3.5-turbo-0125EnglishItaly812 words
degenerate_repetitionPresentFinal dense release
USER
You are a useful assistant that extracts tuples, that we call CLAIM, each contains information of only one cell from an HTML table that will be provided below.
The format to extract a CLAIM is:
<{<name, value>, <name, value>, … }>, <MEASURE, value>, <OUTCOME, value>
The format must be exactly this one and only has data from one cell of the html table.
Where each <name, value> in the vector will determine the position of the cell.
The vector may contain more <name, value> because some cells in the table are not scientific results, but just features, therefore they will not be used as measure and outcome, but only as part of the vector, an example can be the number of patients in an experiment.
Make sure to replicate exactly how the vector is made above.
Where <MEASURE, value> is the value of the MEASURE used in that cell.
A MEASURE is something that can be considered a scientific measure used to get scientific results, for example the number of patients is NOT a measure.
Where <OUTCOME, value> is the actual value, usually a number in the cell.

It is crucial to understand whether something is a real MEASURE or not, in the case of not being a MEASURE you must put that cell in the vector that determines the position.
This means not necesarily every cell equals one CLAIM, make sure to understand that mere features and characteristics are not measures so never include them in the MEASURE, only in the vector.
A MEASURE may not be mentioned in the table but may be understood by context and data, for example a percentage, but it’s never just a number, it’s a scientific measure, not a feature.
Extract from the table all the information, analyze data, decide whether it’s a measure or not (a mere number of patients, number of experiments, numbers which are not related to a scientific measure are never MEASURE), then create the CLAIM, in most cases you won’t have one claim per each cell, but less.
Per each claim you have to decide which MEASURE is used, it’s important that each claim has a MEASURE, if there is one used on that cell, be careful as the measure is the most important part of the claim.
Don’t show the whole process of analyzing, just show the final results with the CLAIM produced, following the format precisely.

Here is the HTML Table:
<html>
 <head>
  <meta charset="utf-8"/>
  <style>
   table, th, td {
                     border: 1px solid black;
                     font-size: 10px;
                   }
  </style>
 </head>
 <body>
  <table frame="hsides" rules="groups" width="100%">
   <thead>
    <tr>
     <td>
      <b>
       Field
      </b>
     </td>
     <td>
      <b>
       Frequency
      </b>
     </td>
     <td>
      <b>
       Percent
      </b>
     </td>
    </tr>
   </thead>
   <tbody>
    <tr>
     <td>
      Non specialist
     </td>
     <td>
      67
     </td>
     <td>
      35.4
     </td>
    </tr>
    <tr>
     <td>
      Oral &amp; maxillofacial surgery
     </td>
     <td>
      37
     </td>
     <td>
      19.6
     </td>
    </tr>
    <tr>
     <td>
      Orthodontics
     </td>
     <td>
      18
     </td>
     <td>
      9.5
     </td>
    </tr>
    <tr>
     <td>
      Restorative
     </td>
     <td>
      15
     </td>
     <td>
      7.9
     </td>
    </tr>
    <tr>
     <td>
      Oral pathology
     </td>
     <td>
      15
     </td>
     <td>
      7.9
     </td>
    </tr>
    <tr>
     <td>
      Community dentistry
     </td>
     <td>
      11
     </td>
     <td>
      5.8
     </td>
    </tr>
    <tr>
     <td>
      Prosthodontics
     </td>
     <td>
      8
     </td>
     <td>
      4.2
     </td>
    </tr>
    <tr>
     <td>
      Oral medicine
     </td>
     <td>
      8
     </td>
     <td>
      4.2
     </td>
    </tr>
    <tr>
     <td>
      Pediatric dentistry
     </td>
     <td>
      7
     </td>
     <td>
      3.7
     </td>
    </tr>
    <tr>
     <td>
      Periodontology
     </td>
     <td>
      3
     </td>
     <td>
      1.6
     </td>
    </tr>
    <tr>
     <td>
      Total
     </td>
     <td>
      189
     </td>
     <td>
      100.0
     </td>
    </tr>
   </tbody>
  </table>
 </body>
</html>


Caption provided for the table:
Field of practice among the participants

Paragraph quoting the table in the document:
About one-third of the participants were non-specialist. Oral and Maxillofacial Surgery, Orthodontics, Restorative and Oral Pathology were the four leading fields of practice among participants that were specialist or specializing (Table 2).

DO NOT IGNORE THE FORMAT, YOU MUST FOLLOW IT PRECISELY.
Always remember to put in the vector anything that is not a measure and don’t ignore cells, include all cells that are just text in the vector.
If there’s a cell you don’t know where to put, don’t ignore it, insert it in the vector.
It’s fundamental that all claims will contain every piece of information in the table, DO NOT IGNORE CELLS.
ASSISTANT
{<Field, Non specialist>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189>
{<Field, Oral & maxillofacial surgery>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189>
{<Field, Orthodontics>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189>
{<Field, Restorative>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189>
{<Field, Oral pathology>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189}
{<Field, Community dentistry>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189}
{<Field, Prosthodontics>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189}
{<Field, Oral medicine>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189}
{<Field, Pediatric dentistry>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189}
{<Field, Periodontology>, <name, value>, <name, value>}, <MEASURE, Total>, <OUTCOME, 189}