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

Shard Start offset Rows Behavior Label Random row JSON API

turns-00040.parquet:21185

6130b45717e58136da815471

turn 1/1gpt-4o-2024-08-06Englishunknown country532 words

degenerate_repetitionAbsentFinal dense release

USER

System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: really disappointed with your customer services team. Ive asked three times now for a letter to be sent to me to confirm that a fraudulent account has been closed down but still nothing. Ask to speak to managers but theyre always in a meeting. #fraud #CustomerExperience
intention: bug report
review: I don't need a dm. Why don't your stores carry what I need for my phone?
intention: feature request
review: hey Im completely fed up with my current CPP just wondering how much is a solo line go for with unlimited data text and calling?
intention: other
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

ASSISTANT

bug report

turns-00040.parquet:21186

a97a36d3d67cb1acc4f541c7

turn 1/1gpt-4o-2024-08-06EnglishUnited States499 words

degenerate_repetitionAbsentFinal dense release

USER

ASSISTANT

other

turns-00040.parquet:21187

6f2a0e02942c36f3a7a75af5

turn 1/1gpt-4o-mini-2024-07-18RussianItaly184 words

degenerate_repetitionAbsentFinal dense release

USER

Нужно письмо на тему я битмейкер DUCK CRAZY BEATS и у меня есть Beats для артистов. Текст должен состоять от 2 до 4 абзаццев. По Английски

ASSISTANT

Subject: Professional Beats Available for Artists

Dear [Artist's Name],

I hope this message finds you well! My name is Duck Crazy Beats, and I am a dedicated beatmaker specializing in creating fresh and innovative instrumentals for artists across various genres. Whether you’re looking for a hard-hitting hip-hop beat, an energetic pop track, or something more experimental, I have a diverse collection of beats that can elevate your musical projects.

I understand the importance of having the perfect sound that resonates with your artistic vision. That’s why I take pride in crafting unique and high-quality beats that not only inspire creativity but also help artists stand out in the competitive music scene. If you’re interested, I would love to share some of my work with you and discuss how we can collaborate to bring your next project to life.

Looking forward to the possibility of working together!

Best regards,  
Duck Crazy Beats  
[Your Contact Information]  
[Your Website/Social Media Links]

turns-00040.parquet:21188

48f9f1594baf7126b8b00c46

turn 1/1gpt-4o-2024-08-06Englishunknown country493 words

degenerate_repetitionAbsentFinal dense release

USER

ASSISTANT

other

turns-00040.parquet:21189

7b259572a9e94ae7893ebcc2

turn 1/1gpt-4o-2024-08-06EnglishUnited States574 words

degenerate_repetitionAbsentFinal dense release

USER

System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: Our operating results are affected over the long term by automotive parts failure rates. These failure rates are impacted by a number of factors outside of our control, including product designs that have resulted in greater reliability, the number of miles driven by consumers, and the average age of vehicles on the road. A reduction in the failure rates of automotive parts would adversely affect our sales and profitability. Our reliance on foreign suppliers for some of the automotive parts we sell to our customers or included in our products presents risks to our business.
Assistant:

ASSISTANT

```json
{
    "relevant_tasks": [
        {
            "task": "Risk Classification",
            "examples": [
                {
                    "input": "The paragraph entails a discussion on risks related to reliance on foreign suppliers for automotive parts.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph does not entail any mention of risks associated with environmental regulations.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Impact Classification",
            "examples": [
                {
                    "input": "The paragraph entails that a reduction in automotive parts failure rates would negatively impact sales and profitability.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph does not entail that an increase in automotive parts failure rates would positively impact employee morale.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Entity Recognition",
            "examples": [
                {
                    "input": "The paragraph entails the recognition of entities such as 'foreign suppliers' and 'automotive parts'.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph does not entail the recognition of an entity such as 'government policies'.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Trend Detection",
            "examples": [
                {
                    "input": "The paragraph entails a trend towards greater reliability in product designs affecting automotive parts failure rates.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph does not entail a trend towards decreasing consumer interest in automotive parts.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Tense Identification",
            "examples": [
                {
                    "input": "The paragraph entails the use of present tense in 'Our reliance on foreign suppliers presents risks to our business'.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph does not entail any use of future tense in describing the impact on sales.",
                    "label": "non-entailment"
                }
            ]
        }
    ]
}
```

turns-00040.parquet:21190

25c918c4657a88e48b067f8b

turn 1/1gpt-4o-2024-08-06EnglishChina505 words

degenerate_repetitionAbsentFinal dense release

USER

ASSISTANT

bug report

turns-00040.parquet:21191

61e1afd939b4cbcf43456253

turn 1/1gpt-4o-2024-08-06EnglishUnited States546 words

degenerate_repetitionAbsentFinal dense release

USER

System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: In light of the continuous pressure on pricing which we have experienced from our large customers, we may not be able to recoup the higher costs of our products due to changes in the prices of raw materials, particularly aluminum, copper, steel, and cardboard. If we are unable to recover a substantial portion of our raw materials from Used Cores returned to us by our customers through the core exchange programs, the prices of Used Cores that we purchase may reflect the impact of changes in the cost of raw materials. Sustained raw material price increases has had a non-material impact on our product costs and profitability to date, but we are unable to determine the overall impact, in the future, at this time.
Assistant:

ASSISTANT

```json
{
    "relevant_tasks": [
        {
            "task": "Risk Classification",
            "examples": [
                {
                    "input": "The paragraph describes the risk of not being able to recoup higher product costs due to price pressures and changes in raw material costs.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph concludes that there is no risk associated with changes in raw material prices.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Uncertainty Identification",
            "examples": [
                {
                    "input": "The paragraph indicates uncertainty about the overall future impact of raw material price changes on profitability.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph provides a definite conclusion about the future impact of raw material price changes.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Entity Recognition",
            "examples": [
                {
                    "input": "The paragraph mentions several specific entities such as aluminum, copper, steel, and cardboard.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph only discusses general concepts without mentioning any specific entities.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Tense Identification",
            "examples": [
                {
                    "input": "The paragraph describes current and potential future impacts of raw material cost changes.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph focuses exclusively on past events regarding raw material costs.",
                    "label": "non-entailment"
                }
            ]
        }
    ]
}
```

turns-00040.parquet:21192

dd8cb4ebaf3d296489bec5e6

turn 1/1gpt-4o-2024-08-06EnglishUnited States494 words

degenerate_repetitionAbsentFinal dense release

USER

ASSISTANT

other

turns-00040.parquet:21193

d4083b82a65467cc19ba67a4

turn 1/1gpt-4o-2024-08-06EnglishUnited States580 words

degenerate_repetitionAbsentFinal dense release

USER

System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: In our remanufacturing processes, we obtain Used Cores, primarily through the core exchange programs with our customers, and component parts from third-party manufacturers. To supplement Used Cores received from our customers we purchase Used Cores from core brokers. Historically, the Used Core returned from customers together with purchases from core brokers have provided us with an adequate supply of Used Cores. If there was a significant disruption in the supply of Used Cores, whether as a result of increased Used Core acquisitions by existing or new competitors or otherwise, our operating activities could be materially and adversely impacted. In addition, a number of the other components used in the remanufacturing process are available from a very limited number of suppliers. We are, as a result, vulnerable to any disruption in component supply, and any meaningful disruption in this supply would materially and adversely impact our operating results.
Assistant:

ASSISTANT

```json
{
    "relevant_tasks": [
        {
            "task": "Risk Classification",
            "examples": [
                {
                    "input": "The paragraph implies a risk associated with a disruption in the supply of Used Cores and other components, potentially affecting the company’s operations.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph describes a stable and resilient supply chain with no foreseeable risks to the company’s operations.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Entity Recognition",
            "examples": [
                {
                    "input": "The paragraph mentions entities such as 'Used Cores', 'core exchange programs', 'core brokers', and 'third-party manufacturers'.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph includes named entities like 'Core Exchange Ltd.' and 'Brokers Co.'",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Impact Classification",
            "examples": [
                {
                    "input": "The paragraph indicates that disruptions in component supply could have a material and adverse impact on operating results.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph states that disruptions in component supply would have negligible effects on operating results.",
                    "label": "non-entailment"
                }
            ]
        },
        {
            "task": "Sector Identification",
            "examples": [
                {
                    "input": "The paragraph pertains to the remanufacturing sector, focusing on the supply chain of Used Cores and components.",
                    "label": "entailment"
                },
                {
                    "input": "The paragraph is related to the technology and software development sector.",
                    "label": "non-entailment"
                }
            ]
        }
    ]
}
```

turns-00040.parquet:21194

f7d761fce48d8873f0467fa5

turn 1/1gpt-4o-mini-2024-07-18Chineseunknown country231 words

degenerate_repetitionAbsentFinal dense release

USER

我將會給定一個 [query], 以及可以參考的文件, 每個文件會有編號, 如:[25], 文件編號後面會附上文件的內容
你的任務是參考這些文件，找出 [query] 的答案最可能是在哪個文件中, 並且輸出文件編號即可
如有文件 [17], [18], [19], 你認為答案在文件 [19] 中, 即輸出 19
也就是說你的輸出只要包含一個數字 N 就好, 不需要有更多額外的輸出

要保人的住所有變更時，應以何種方式通知本公司?
文件[148], 內容如下:
南山人壽新福愛小額終身壽險_MPL3
保險公司者，不得對抗保險公司。
前項受益人的變更，於要保人檢具申請書及被保險人的同意書（要、被保險人為
同一人時為申請書或電子申請文件）送達本公司時，本公司應即予批註或發給批
註書。
「身故保險金」或喪葬費用保險金受益人同時或先於被保險人本人身故，除要保
人已另行指定受益人外，以被保險人身故時之法定繼承人為本契約受益人。
前項法定繼承人之順序及應得保險金之比例適用民法繼承編相關規定。
第二十九條 變更住所
要保人的住所有變更時，應即以書面或其他約定方式通知本公司。
要保人不為前項通知者，本公司之各項通知，得以本契約所載要保人之最後住所
發送之。
第三十條 時效
由本契約所生的權利，自得為請求之日起，經過兩年不行使而消滅。
第三十一條 批註
本契約內容的變更，或記載事項的增刪，除第二十八條規定者外，應經要保人與
本公司雙方書面或其他約定方式同意，並由本公司即予批註或發給批註書。
第三十二條 管轄法院
因本契約涉訟者，同意以要保人住所地地方法院為第一審管轄法院，要保人的住
所在中華民國境外時，以本公司總公司所在地地方法院為第一審管轄法院。但不
得排除消費者保護法第四十七條及民事訴訟法第四百三十六條之九小額訴訟管轄
法院之適用。
第 9 頁，共 11 頁
文件[63], 內容如下:
南山人壽樂活洋溢醫療終身保險_TPHI5
第二十五條 保險單借款及契約效力的停止
要保人繳足保險費累積達有保單價值準備金時，要保人得向本公司申請保險單借
款，其可借金額上限為借款當日保單價值準備金之一定百分比，其比率請詳附表
四，未償還之借款本息，超過其保單價值準備金時，本契約效力即行停止。但本
公司應於效力停止日之三十日前以書面通知要保人。
本公司未依前項規定為通知時，於本公司以書面通知要保人返還借款本息之日起
三十日內要保人未返還者，保險契約之效力自該三十日之次日起停止。
第二十六條 不分紅保險單
本保險為不分紅保單，不參加紅利分配，並無紅利給付項目。
第二十七條 年齡的計算及錯誤的處理
被保險人的投保年齡，以足歲計算，但未滿一歲的零數超過六個月者，加算一歲，
要保人在申請投保時，應將被保險人的出生年月日在要保書填明。
被保險人的投保年齡發生錯誤時，依下列規定辦理：
一、真實投保年齡較本公司保險費率表所載最高年齡為大者，本契約無效，其已
繳保險費無息退還要保人。
二、因投保年齡的錯誤，而致溢繳保險費者，本公司無息退還溢繳部分的保險費
。但在發生保險事故後始發覺且其錯誤發生在本公司者，本公司按原繳保險
費與應繳保險費的比例提高「單位日額」，而不退還溢繳部分的保險費。
三、因投保年齡的錯誤，而致短繳保險費者，要保人得補繳短繳的保險費或按照
所付的保險費與被保險人的真實年齡比例減少「單位日額」。但在發生保險
事故後始發覺且其錯誤不可歸責於本公司者，要保人不得請求補繳短繳的保
險費。
前項第一款、第二款前段情形，其錯誤原因歸責於本公司者，應加計利息退還保
險費，其利息按本公司退還保險費當時本保單辦理保險單借款之利率與民法第二
百零三條法定週年利率兩者取其大之值計算。
第二十八條 保險事故的通知與保險金的申請時間
要保人、被保險人或受益人應於知悉本公司應負保險責任之事故後十日內通知本
公司，並於通知後儘速檢具所需文件向本公司申請給付保險金。
本公司應於收齊前項文件後十五日內給付之。但因可歸責於本公司之事由致未在
前述約定期限內為給付者，應按年利一分加計利息給付。
第二十九條 失蹤處理
被保險人在本契約有效期間內失蹤者，如經法院宣告死亡時，本公司根據判決內
所確定死亡時日為準，依第十五條約定退還「所繳保險費加計利息」或給付「身
故保險金」或喪葬費用保險金；如要保人或受益人能提出證明文件，足以認為被
保險人極可能因意外傷害事故而死亡者，本公司應依意外傷害事故發生日為準，
依第十五條約定退還「所繳保險費加計利息」或給付「身故保險金」或喪葬費用
保險金。
前項情形，本公司退還「所繳保險費加計利息」或給付「身故保險金」或喪葬費
用保險金後，如發現被保險人生還時，要保人、應得之人或受益人應將該筆已領
之退還已繳保險費或「所繳保險費加計利息」或「身故保險金」或喪葬費用保險
金歸還本公司，其間若有應給付保險金之情事發生者，仍應予給付。但有應繳之
保險費，本公司仍得予以扣除。
第三十條 受益人的指定及變更
本契約第九條至第十二條保險金之受益人為被保險人本人，本公司不受理其指定
第 11 頁，共 46 頁南山人壽樂活洋溢醫療終身保險_TPHI5
及變更。
除前項約定外，要保人得依下列規定指定或變更受益人，並應符合指定或變更當
時法令之規定：
一、於訂立本契約時，經被保險人同意指定受益人。如未指定者，則以要保人本
人為本契約「祝壽保險金」受益人。
二、於保險事故發生前經被保險人同意變更受益人，如要保人未將前述變更通知
保險公司者，不得對抗保險公司。
前項受益人的變更，於要保人檢具申請書及被保險人的同意書（要、被保險人為
同一人時為申請書或電子申請文件）送達本公司時，本公司應即予批註或發給批
註書。
受益人同時或先於被保險人本人身故，除要保人已另行指定受益人外，以被保險
人之法定繼承人為本契約受益人。
前項法定繼承人之順序及應得保險金之比例適用民法繼承編相關規定。
第三十一條 第九條、第十條及第十二條保險金的申領
受益人申領本契約第九條、第十條及第十二條保險金時，應檢具下列文件：
一、保險金申請書。
二、保險單或其謄本。
三、醫療診斷書或住院證明。（但要保人或被保險人為醫師時，不得為被保險人
出具診斷書或住院證明。）
四、受益人的身分證明。
受益人申領保險金時，本公司基於審核保險金之需要，得徵詢其他醫師之醫學專
業意見，並得經受益人同意調閱被保險人之就醫相關資料。因此所生之費用由本
公司負擔。但不因此延展本公司依第二十八條約定應給付之期限。
第三十二條 未住院健康鼓勵保險金的申領
受益人申領「未住院健康鼓勵保險金」時，應檢具下列文件：
一、保險單或其謄本。
二、保險金申請書。
三、受益人的身分證明。
第三十三條 一至六級失能豁免保險費的申請
要保人應於知悉有得豁免保險費之事由時以書面通知本公司，並於通知後儘速檢
具下列文件向本公司申請豁免保險費：
一、保險單或其謄本。
二、保險金申請書。
三、失能診斷書。
要保人申請豁免保險費時，本公司基於審核之需要，得對被保險人的身體予以檢
驗，另得徵詢其他醫師之醫學專業意見，並得經被保險人同意調閱被保險人之就
醫相關資料。因此所生之費用由本公司負擔。
第三十四條 祝壽保險金的申領
受益人申領「祝壽保險金」時，應檢具下列文件：
一、保險單或其謄本。
二、保險金申請書。
三、受益人的身分證明。
第三十五條 身故保險金或喪葬費用保險金的申領
受益人申領「身故保險金」或喪葬費用保險金時應檢具下列文件：
第 12 頁，共 46 頁
文件[62], 內容如下:
南山人壽年年滿利利率變動型還本終身保險（定期給付型）_2BTE2
約定給付保單價值準備金予應得之人，而於給付保單價值準備金後，本契約效力
即行終止。
被保險人因下列原因致成身故時，本公司不負給付第二十三條「大眾運輸意外身
故保險金」或喪葬費用保險金的責任：
一、要保人、被保險人的故意行為。
二、被保險人犯罪行為。
三、被保險人飲酒後駕（騎）車，其吐氣或血液所含酒精成份超過道路交通法令
規定標準者。
四、戰爭（不論宣戰與否）、內亂及其他類似的武裝變亂。但契約另有約定者不
在此限。
五、因原子或核子能裝置所引起的爆炸、灼熱、輻射或污染。但契約另有約定者
不在此限。
第一項第一款、第三項第一款（除被保險人的故意行為外）及第二十八條情形致
被保險人成附表二所列完全失能等級之一時，本公司按第二十一條的約定給付
「完全失能保險金」。
第二十八條 受益人之受益權
受益人故意致被保險人於死或雖未致死者，喪失其受益權。
前項情形，如因該受益人喪失受益權，而致無受益人受領「身故保險金」、「大
眾運輸意外身故保險金」或喪葬費用保險金時，其「身故保險金」、「大眾運輸
意外身故保險金」或喪葬費用保險金作為被保險人遺產。如有其他受益人者，喪
失受益權之受益人原應得之部分，按其他受益人原約定比例分歸其他受益人。
第二十九條 欠繳保險費或未還款項的扣除
本公司給付各項保險金、增值回饋分享金、解約金、返還保單價值準備金或退還
已繳保險費時，如要保人有欠繳保險費（包括經本公司墊繳的保險費）或保險單
借款未還清者，本公司得先抵銷上述欠款及扣除其應付利息後給付其餘額。
第三十條 減少基本保額及累計增額繳清保險基本保額
要保人在本契約「保障期間」內，得申請減少「基本保額」及「累計增額繳清保
險基本保額」，本公司應按下列順序依序減去，但是減額後的「基本保額」，不
得低於本保險最低承保金額，其減少部分依第九條契約終止之約定處理：
一、依第十四條約定之「累計增額繳清保險基本保額」。
二、「基本保額」。
第三十一條 減額繳清保險
要保人繳足保險費累積達有保單價值準備金時，要保人得以當時「基本保額」對
應之保單價值準備金扣除營業費用後的數額作為一次繳清的躉繳保險費，向本公
司申請改保同類保險的「減額繳清保險」，其「基本保額」如繳清保險基本保額
附表。要保人變更為「減額繳清保險」後，不必再繼續繳保險費，本契約繼續有
效。其保險範圍與原契約同，但「基本保額」以減額繳清保險基本保額為準。
要保人選擇改為「減額繳清保險」當時，倘有增值回饋分享金、保險單借款或欠
繳、墊繳保險費的情形，本公司將以當時「基本保額」對應之保單價值準備金加
上本公司應給付的增值回饋分享金扣除欠繳保險費或借款本息或墊繳保險費本
息及營業費用後的淨額辦理。
本條營業費用以原「基本保額」之百分之一或「原基本保額所對應之保單價值準
備金與解約金之差額」，兩者較小者為限。
第三十二條 展期定期保險
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