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### Instruction:
Extract the cause and effect entities from the following sentence:
R-2.3.2-5: During the nominal science acquisition phase, the following spacecraft scale distances shall be established (In GSE coordinates: x is sun-Earth direction, y is East/West, z is North/South
### Assistant:
NOT_RELEVANT: (In GSE coordinates: x is sun-Earth direction, y is East/West, z is North/South.
KEYWORD: During
VARIABLE: the following spacecraft scale distances
CAUSE_1: the nominal science acquisition phase
CONDITION: shall be established
EFFECT_1: the following spacecraft scale distances shall be established
### END
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### Instruction:
Extract the cause and effect entities from the following sentence:
During the science acquisition phase, one scan shall be performed from 6,000 km (0.5y + commissioning time) to 3,000 km (0.5y) to 15,000 km (1y) to 6,000 km (till end of mission)
### Assistant:
KEYWORD: During
VARIABLE: one scan
CAUSE_1: the science acquisition phase
CONDITION: to 15,000 km
EFFECT_1: to 6,000 km
NOT_RELEVANT: (till end of mission)
### END
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### Instruction:
Extract the cause and effect entities from the following sentence:
R-2.3.9-3: All S/C shall be capable to receive and acknowledge commands from the ground at all times when communication links can be established
### Assistant:
NOT_RELEVANT: R-2.3.9-3:
VARIABLE: communication links
CONDITION: can be established
AND: and
EFFECT_1: All S/C shall be capable to receive
KEYWORD: when
EFFECT_2: acknowledge commands from the ground at all times
CAUSE_1: communication links can be established
### END
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### Instruction:
Extract the cause and effect entities from the following sentence:
R-2.3.10-5: Acquisition of housekeeping data shall be performed for all instruments and the platform subsystems, such that their state of health can be assessed at all times
### Assistant:
NOT_RELEVANT: R-2.3.10-5:
VARIABLE: all instruments
CONDITION: can be assessed at all times
AND: and
KEYWORD: for
CAUSE_1: Acquisition of housekeeping data shall be performed
CAUSE_3: the platform subsystems
EFFECT_1: their state of health can be assessed at all times
CAUSE_2: all instruments
### END
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### Instruction:
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Where this can be accomplished without risk to satellite safety such switching shall enable the continuity of the mission timeline and performance
### Assistant:
KEYWORD: Where
VARIABLE: the continuity of the mission timeline
CONDITION: shall enable
AND: and
CAUSE_1: this can be accomplished without risk to satellite safety
CAUSE_2: such switching
EFFECT_1: shall enable the continuity of the mission timeline
EFFECT_2: performance
### END
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### Instruction:
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If the vehicles require additional post-manufacturing equipment, a declaration that required transformations have taken place should be submitted with the quotation
### Assistant:
KEYWORD: If
VARIABLE: a declaration that required transformations have taken place
CONDITION: should be submitted with the quotation
CAUSE_1: the vehicles require additional post-manufacturing equipment
EFFECT_1: a declaration that required transformations have taken place should be submitted with the quotation
### END
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### Instruction:
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An international coordination mechanism among key actors worldwide (users, producers, science, regional/national experts) is essential to ensure that land cover products are accepted internationally and by the UNFCCC
### Assistant:
VARIABLE: land cover products
CONDITION: by the UNFCCC
AND: and
KEYWORD: to ensure that
EFFECT_1: land cover products are accepted internationally
EFFECT_2: by the UNFCCC
CAUSE_1: is essential
NOT_RELEVANT: (users, producers, science, regional/national experts)
### END
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### Instruction:
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The importance of these issues requires continuous monitoring systems and data
### Assistant:
VARIABLE: data
CONDITION: requires
CAUSE_1: The importance of these issues
AND: and
EFFECT_1: requires continuous monitoring systems
EFFECT_2: data
### END
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### Instruction:
Extract the cause and effect entities from the following sentence:
This broad assessment of user requirements ensures that the full range of needs are considered and understood for deriving the detailed product specifications
### Assistant:
VARIABLE: the full range of needs
CONDITION: understood for deriving the detailed product specifications
CAUSE_1: This broad assessment of user requirements
KEYWORD: ensures that
AND: and
EFFECT_1: understood for deriving the detailed product specifications
### END
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### Instruction:
Extract the cause and effect entities from the following sentence:
This broad assessment of user requirements ensures that the full range of needs are considered and understood for deriving the detailed product specification
### Assistant:
VARIABLE: the full range of needs
CONDITION: are considered
CAUSE_1: This broad assessment of user requirements
KEYWORD: ensures that
AND: and
EFFECT_1: the full range of needs are considered
EFFECT_2: understood for deriving the detailed product specification
### END
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### Instruction:
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LCCS classifiers enable better compatibility to be achieved between existing datasets and for future global monitoring systems
### Assistant:
VARIABLE: better compatibility
KEYWORD: enable
CAUSE_1: LCCS classifiers
CONDITION: for future global monitoring systems
AND: and
EFFECT_1: better compatibility to be achieved between existing datasets
EFFECT_2: for future global monitoring systems
### END
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### Instruction:
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However, the independent accuracy assessment for monitoring land cover as ECV poses additional requirements and challenges
### Assistant:
NOT_RELEVANT: However,
VARIABLE: the
CAUSE_1: the independent accuracy assessment for monitoring land cover as ECV
AND: and
CONDITION: independent
EFFECT_1: poses additional requirements
EFFECT_2: challenges
### END
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### Instruction:
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For the future there is need to develop the foundations and start implementing on operational monitoring that ensures that progressing annual global land cover datasets can assessed consecutively
### Assistant:
KEYWORD: that ensures that
VARIABLE: operational monitoring
CONDITION: start implementing on
EFFECT_1: progressing annual global land cover datasets can assessed consecutively
AND: and
CAUSE_1: there is need to develop the foundations
CAUSE_2: start implementing on operational monitoring
NOT_RELEVANT: For the future
### END
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### Instruction:
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There is need for an independent quality assessment to ensure that the required standards are met, and that uncertainties are quantified and reduced as far as practicable
### Assistant:
KEYWORD: that
VARIABLE: quality assessment
CONDITION: independent
EFFECT_1: the required standards are met
AND: and
EFFECT_2: uncertainties are quantified
EFFECT_3: reduced as far as practicable
CAUSE_1: independent quality assessment
NOT_RELEVANT: There is need for an
### END
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### Instruction:
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This mechanism should provide a comparative assessment and validation of individual products and work towards synergy to ensure that a common framework is used for global assessments, and that the “best global estimates” are made available based on the current stage of knowledge, data and information
### Assistant:
VARIABLE: the “best global estimates”
CONDITION: are made available based on the current stage of knowledge, data and information
AND: and
CAUSE_1: This mechanism should provide a comparative assessment
CAUSE_2: validation of individual products
CAUSE_3: work towards synergy
KEYWORD: that
EFFECT_1: a common framework is used for global assessments
EFFECT_2: the “best global estimates” are made available based on the current stage of knowledge, data and information
### END
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### Instruction:
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As part of this, to ensure full documentation, transparency and scientific stewardship in the generation (and update) of FCDRs and ECV products, the GCOS Steering Committee recommends that data producers pay particular attention to the 12 needs enumerated below and provided in the Guideline for the Generation of Datasets and Products Meeting GCOS Requirements (GCOS 2010a)
### Assistant:
VARIABLE: of FCDRs and ECV products
CONDITION: recommends that data producers pay particular attention to the 12 needs enumerated below and provided in the Guideline for the Generation of Datasets and Products Meeting GCOS Requirements (GCOS 2010a)
EFFECT_1: to ensure full documentation
NOT_RELEVANT: (and update)
AND: and
EFFECT_2: transparency
EFFECT_3: of FCDRs and ECV products
CAUSE_1: the GCOS Steering Committee recommends that data producers pay particular attention to the 12 needs enumerated below and provided in the Guideline for the Generation of Datasets and Products Meeting GCOS Requirements (GCOS 2010a).
### END
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### Instruction:
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The first set of observations enables quantification of the distribution and variability of CO2 fluxes between the Earth's surface and the atmosphere
### Assistant:
VARIABLE: variability of CO2 fluxes between the Earth's surface and the atmosphere
CAUSE_1: The first set of observations
CONDITION: enables
AND: and
EFFECT_1: quantification of the distribution
EFFECT_2: variability of CO2 fluxes between the Earth's surface and the atmosphere
### END
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### Instruction:
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It is critical to harmonize the widely varying methodologies for inventory and analysis, in order to synthesize carbon estimates based on national forest inventories
### Assistant:
KEYWORD: in order
VARIABLE: the widely varying methodologies
CONDITION: for inventory and analysis
EFFECT_1: to synthesize carbon estimates based on national forest inventories
NOT_RELEVANT: It is critical
CAUSE_1: to harmonize the widely varying methodologies for inventory and analysis
### END
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### Instruction:
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Fire distribution (hot spots) and burned area extent, to estimate the fluxes of carbon that are emitted during fires
### Assistant:
VARIABLE: the fluxes of carbon that are emitted during fires
AND: and
CONDITION: to estimate
EFFECT_1: to estimate the fluxes of carbon that are emitted during fires
CAUSE_2: burned area extent
CAUSE_1: Fire distribution
NOT_RELEVANT: (hot spots)
### END
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### Instruction:
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Also differences in spatial and temporal resolution are regarded as reasons for interoperability problems
### Assistant:
VARIABLE: differences in spatial
EFFECT_1: interoperability problems
KEYWORD: as reasons for
AND: and
CONDITION: are regarded
NOT_RELEVANT: Also
CAUSE_1: differences in spatial
CAUSE_2: temporal resolution are regarded
### END
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### Instruction:
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Furthermore, the allocation of model parameters and the transformation of land cover data to other information, due to interpolation issues, remains a source of inaccuracy
### Assistant:
KEYWORD: due to
VARIABLE: the transformation of land cover data to other information
CAUSE_1: interpolation issues
AND: and
CONDITION: remains a source of inaccuracy
NOT_RELEVANT: Furthermore
EFFECT_1: the allocation of model parameters
EFFECT_2: remains a source of inaccuracy
### END
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### Instruction:
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For one user where models are applied to different spatial extends, the accuracy of the land cover products is rated very good to moderate
### Assistant:
KEYWORD: For
VARIABLE: one user
CONDITION: is rated very good to moderate
CAUSE_2: models are applied to different spatial extends
CAUSE_1: one user
EFFECT_1: the accuracy of the land cover products is rated very good to moderate
### END
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### Instruction:
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Going from current to future model requirements, a trend towards an increase in required spatial resolution of land cover datasets can be identified (Figure 14)
### Assistant:
VARIABLE: a trend towards an increase in required spatial resolution of land cover datasets
CONDITION: can be identified
CAUSE_1: Going from current to future model requirements
NOT_RELEVANT: (Figure 14)
EFFECT_1: a trend towards an increase in required spatial resolution of land cover datasets can be identified
### END
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### Instruction:
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However, the introduction of new modeling approaches will require temporal frequencies for some classes up to a monthly resolution
### Assistant:
VARIABLE: temporal frequencies for some classes up to a monthly resolution
CONDITION: will require
NOT_RELEVANT: However
CAUSE_1: the introduction of new modeling approaches
EFFECT_1: will require temporal frequencies for some classes up to a monthly resolution
### END
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### Instruction:
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Furthermore, in order to improve current models and feed improved model approaches within 5 years, higher demands are put on the temporal ranges available of input data
### Assistant:
NOT_RELEVANT: Furthermore,
KEYWORD: in order
VARIABLE: higher demands
CONDITION: are put on the temporal ranges available of input data
AND: and
EFFECT_1: to improve current models
EFFECT_2: feed improved model approaches within 5 years
CAUSE_1: higher demands are put on the temporal ranges available of input data
### END
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### Instruction:
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For some global models, temporal ranges up to 10.000 years will be required
### Assistant:
VARIABLE: some global models
CONDITION: will be required
EFFECT_1: temporal ranges up to 10.000 years will be required
CAUSE_1: some global models
NOT_RELEVANT: For
### END
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### Instruction:
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To produce accurate model output with relatively short simulation steps, historical data of high quality (spatial and temporal resolution) is required
### Assistant:
VARIABLE: historical data of high quality
CONDITION: is required
EFFECT_1: To produce accurate model output with relatively short simulation steps
NOT_RELEVANT: (spatial and temporal resolution)
CAUSE_1: is required
### END
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### Instruction:
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For different land surface parameters the pattern of class similarity is rather different
### Assistant:
VARIABLE: the pattern of class similarity
CONDITION: is rather different
KEYWORD: For
CAUSE_1: different land surface parameters
EFFECT_1: the pattern of class similarity is rather different
### END
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### Instruction:
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This highlights that the relative importance and thus accuracy of land cover categories for model parameterization varies depending on what model parameter is estimated from the data
### Assistant:
NOT_RELEVANT: This highlights that
VARIABLE: what model parameter
EFFECT_1: the relative importance
AND: and
KEYWORD: depending on
CONDITION: is estimated from the data
EFFECT_2: accuracy of land cover categories for model parameterization varies
CAUSE_1: what model parameter is estimated from the data
### END
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### Instruction:
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The areas with pink table cells have the highest average similarities among all land surface parameters
### Assistant:
VARIABLE: The areas
KEYWORD: with
CONDITION: have the highest average similarities among all land surface parameters
CAUSE_1: pink table cells
EFFECT_1: have the highest average similarities among all land surface parameters
### END
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### Instruction:
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Within the modeling process, land cover products are also adopted to determine land surface parameters which are then use to initialize the climate models
### Assistant:
CAUSE_1: the modeling process
VARIABLE: the modeling process
CONDITION: are then use to initialize the climate models
CAUSE_2: land cover products are also adopted
EFFECT_1: to determine land surface parameters
KEYWORD: which
EFFECT_2: are then use to initialize the climate models
### END
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### Instruction:
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In a more general sense it is stated that parameters must be used that are both mechanistically important and measurable (Ostle et al
### Assistant:
NOT_RELEVANT: (Ostle et al
KEYWORD: that
CONDITION: are
AND: both
VARIABLE: parameters
EFFECT_1: parameters must be used
CAUSE_1: mechanistically important
CAUSE_2: measurable
### END
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### Instruction:
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Per definition, it is not possible to correctly interpret carbon cycle simulations if the overall-, user-, and producer accuracy is not known (Jung et al
### Assistant:
NOT_RELEVANT: (Jung et al
KEYWORD: if
VARIABLE: producer accuracy
CONDITION: known
EFFECT_1: it is not possible to correctly interpret carbon cycle simulations
AND: and
CAUSE_3: producer accuracy is not known
CAUSE_1: the overall-
CAUSE_2: user-
NEGATION: is not
### END
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### Instruction:
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To advance scientific understanding and enhance data- and model integration, the earth system modeling and integrated assessment modeling communities have to collaborate closely with the remote sensing community (Hibbard et al
### Assistant:
VARIABLE: integrated assessment modeling communities
CONDITION: have to collaborate closely with the remote sensing community
EFFECT_1: To advance scientific understanding
AND: and
EFFECT_2: enhance data-
EFFECT_3: model integration
NOT_RELEVANT: (Hibbard et al
CAUSE_1: the earth system modeling
CAUSE_2: integrated assessment modeling communities have to collaborate closely with the remote sensing community
### END
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### Instruction:
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In addition, it is stated that without accounting for historical land cover changes, observed atmosphere CO2 growth cannot be explained (Brovkin et al
### Assistant:
NOT_RELEVANT: (Brovkin et al
NEGATION: cannot
VARIABLE: observed atmosphere CO2 growth
CONDITION: be explained
CAUSE_1: without accounting for historical land cover changes
EFFECT_1: observed atmosphere CO2 growth cannot be explained
### END
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### Instruction:
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Linked to the requirement for earth system modeling to incorporate land cover change, the decline in land suitability due to soil erosion, acidification and salinization also need to be taken into account (Ramankutty et al
### Assistant:
VARIABLE: salinization
KEYWORD: due to
AND: and
CAUSE_1: soil erosion
CAUSE_2: acidification
CAUSE_3: salinization
EFFECT_1: also need to be taken into account
CONDITION: also need to be taken into account
NOT_RELEVANT: (Ramankutty et al.
### END
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### Instruction:
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For the long term (> 5 years), defined requirements are strongly process based
### Assistant:
VARIABLE: term
NOT_RELEVANT: For
CONDITION: long
CAUSE_1: the long term
EFFECT_1: defined requirements are strongly process based
### END
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### Instruction:
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Nitrogen supply from soil organic matter is not known accurately and introduces uncertainty (Ostle et al
### Assistant:
VARIABLE: Nitrogen supply
CONDITION: introduces uncertainty
CAUSE_1: Nitrogen supply from soil organic matter
AND: and
NOT_RELEVANT: (Ostle et al
EFFECT_1: is not known accurately
EFFECT_2: introduces uncertainty
NEGATION: is not
### END
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### Instruction:
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Due to an increase in greenhouse gases the area of land that is cultivable might increase, but yields might decrease
### Assistant:
KEYWORD: Due to
VARIABLE: yields
CONDITION: might decrease
CAUSE_1: an increase in greenhouse gases
AND: but
EFFECT_1: the area of land that is cultivable might increase
EFFECT_2: yields might decrease
### END
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### Instruction:
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Consistency is the key requirement and thus one fundamental (land cover) dataset is the base for series parameters
### Assistant:
VARIABLE: dataset
CONDITION: is the base for series parameters
AND: and
KEYWORD: thus
CAUSE_1: Consistency is the key requirement
EFFECT_1: dataset is the base for series parameters
NOT_RELEVANT: (land cover)
### END
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### Instruction:
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This puts more burden on the accuracy of the land cover data since related errors propagate to all parameters
### Assistant:
KEYWORD: since
VARIABLE: This
CONDITION: puts more burden on the accuracy of the land cover data
CAUSE_1: related errors propagate to all parameters
EFFECT_1: This puts more burden on the accuracy of the land cover data
### END
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### Instruction:
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More process oriented models need less data for input/calibration but more for validation of outputs
### Assistant:
VARIABLE: more for validation of outputs
CONDITION: need
CAUSE_1: More process oriented models
AND: but
EFFECT_1: need less data for input/calibration
EFFECT_2: more for validation of outputs
### END
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### Instruction:
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Given the fact that users require a suite of different types of land cover categories (or plant functional types) for model parameterization that varies with type of model and modeling approach, any land cover product will need to provide some flexibility in responding to these different thematic needs
### Assistant:
KEYWORD: Given the fact that
VARIABLE: any land cover product
CONDITION: for model parameterization that varies with type of model and modeling approach
CAUSE_1: for model parameterization that varies with type of model and modeling approach
EFFECT_1: any land cover product will need to provide some flexibility in responding to these different thematic needs
NOT_RELEVANT: (or plant functional types)
### END
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### Instruction:
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However, to include these variables into climate models more adequate formats would be required which allow usage in scripting
### Assistant:
NOT_RELEVANT: However,
VARIABLE: more adequate formats
CONDITION: allow usage in scripting
EFFECT_1: to include these variables into climate models
CAUSE_1: more adequate formats would be required
CAUSE_2: allow usage in scripting
KEYWORD: which
### END
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### Instruction:
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In order to provide a comprehensive overview of the user requirements for the different ECVs, ESA has provided a standard template for presentation
### Assistant:
KEYWORD: In order
VARIABLE: ESA
CONDITION: has provided a standard template for presentation
EFFECT_1: to provide a comprehensive overview of the user requirements for the different ECVs
CAUSE_1: ESA has provided a standard template for presentation
### END
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### Instruction:
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For efficiency reasons, a different approach has been presented by Tessella
### Assistant:
VARIABLE: a different approach
CONDITION: has been presented by Tessella
CAUSE_1: efficiency reasons
KEYWORD: For
EFFECT_1: a different approach has been presented by Tessella
### END
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### Instruction:
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Where necessary, user requirements defined in different stages will be identified as such
### Assistant:
VARIABLE: user requirements
CONDITION: defined in different stages
KEYWORD: Where
CAUSE_1: necessary
EFFECT_1: will be identified as such
CAUSE_2: defined in different stages
### END
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### Instruction:
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As the work has a research element, and project decisions will be made based on produced results during the project, it is difficult to estimate precisely how long the development of each stage will take
### Assistant:
KEYWORD: As
VARIABLE: it
CONDITION: is difficult to estimate precisely how long the development of each stage will take
CAUSE_1: the work has a research element
AND: and
CAUSE_2: project decisions will be made based on produced results during the project
EFFECT_1: it is difficult to estimate precisely how long the development of each stage will take
### END
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### Instruction:
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As both these systems are open source, and fall under the GNU Lesser General Public License, they can be used as a starting point for creating the emulator specified in this project
### Assistant:
KEYWORD: As
VARIABLE: they
CONDITION: can be used as a starting point for creating the emulator specified in this project
AND: and
CAUSE_1: both these systems are open source
CAUSE_2: fall under the GNU Lesser General Public License
EFFECT_1: they can be used as a starting point for creating the emulator specified in this project
### END
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### Instruction:
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Once an initial version of the system is produced that fulfils the above capabilities, it will be extended with a library of emulated components, and a controller to interconnect these components
### Assistant:
KEYWORD: that
VARIABLE: it
CONDITION: a controller to interconnect these components
CAUSE_1: an initial version of the system is produced
CAUSE_2: fulfils the above capabilities
AND: and
EFFECT_1: it will be extended with a library of emulated components
EFFECT_2: a controller to interconnect these components
### END
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### Instruction:
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More experienced users can be expected to install the operating systems required for document access, as well as installation of software packages, once provided with the correct environment
### Assistant:
VARIABLE: installation of software packages
CONDITION: provided with
CAUSE_1: More experienced users
KEYWORD: once
CAUSE_2: provided with the correct environment
AND: as well as
EFFECT_1: can be expected to install the operating systems required for document access
EFFECT_2: installation of software packages
### END
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### Instruction:
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Interchanging modules within one environment to test and compare settings can be expected to lead to various configurations
### Assistant:
KEYWORD: to lead to
EFFECT_1: various configurations
CONDITION: compare settings
VARIABLE: configurations
AND: and
CAUSE_1: Interchanging modules within one environment to test
CAUSE_2: compare settings
### END
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### Instruction:
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Deferment of certain DUACS characteristics to a Service Management Plan, necessitates examination of the Service Management Plan during Requirements Analysis
### Assistant:
VARIABLE: Requirements Analysis
CONDITION: necessitates
KEYWORD: during
CAUSE_1: Deferment of certain DUACS characteristics to a Service Management Plan
EFFECT_1: necessitates examination of the Service Management Plan
CAUSE_2: Requirements Analysis
### END
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### Instruction:
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We analyse the PSAD [RD 3] to support the construction of the System Requirements Baseline
### Assistant:
VARIABLE: the construction of the System Requirements Baseline
CONDITION: to support
CAUSE_1: We analyse the PSAD
EFFECT_1: to support the construction of the System Requirements Baseline
NOT_RELEVANT: [RD 3]
### END
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### Instruction:
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Such high level production chain system requirements are ded are satisfiable if and only if their constituent system requirements are entirely satisfied
### Assistant:
KEYWORD: if and only if
VARIABLE: Such high level production chain system requirements
CONDITION: are ded
CAUSE_1: their constituent system requirements are entirely satisfied
EFFECT_1: Such high level production chain system requirements are ded
EFFECT_2: are satisfiable
### END
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### Instruction:
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In nominal case, input and auxiliary data are present and the system acquire them
### Assistant:
VARIABLE: the system
CONDITION: acquire them
KEYWORD: In
AND: and
CAUSE_1: nominal case
EFFECT_1: input
EFFECT_2: auxiliary data are present
EFFECT_3: the system acquire them
### END
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### Instruction:
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The products of degraded quality are not reprocessed but new products will use the new Level 2 data once they have been acquired
### Assistant:
KEYWORD: once
VARIABLE: new products
CONDITION: will use the new Level 2 data
CAUSE_1: they have been acquired
NEGATION: are not
EFFECT_1: The products of degraded quality are not reprocessed
EFFECT_2: new products will use the new Level 2 data
AND: but
### END
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### Instruction:
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When the delay is expired, the support operator is automatically warned that the data flow is too late
### Assistant:
KEYWORD: When
VARIABLE: the support operator
CONDITION: is automatically warned that the data flow is too late
CAUSE_1: the delay is expired
EFFECT_1: the support operator is automatically warned that the data flow is too late
### END
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### Instruction:
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The incident has to be reported to the Top Level Service Desk through the SL TAC Service Desk since it impacts the products available for the users
### Assistant:
KEYWORD: since
VARIABLE: The incident
CONDITION: has to be reported to the Top Level Service Desk through the SL TAC Service Desk
CAUSE_1: it impacts the products available for the users
EFFECT_1: The incident has to be reported to the Top Level Service Desk through the SL TAC Service Desk
### END
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### Instruction:
Extract the cause and effect entities from the following sentence:
This error can be corrected by a new acquisition of the input flow that was initially corrupted (not detected at the acquisition level but at the step of the input checks)
### Assistant:
VARIABLE: the input flow
CONDITION: was initially corrupted
EFFECT_1: This error can be corrected
KEYWORD: that
CAUSE_1: a new acquisition of the input flow
NOT_RELEVANT: (not detected at the acquisition level but at the step of the input checks)
CAUSE_2: was initially corrupted
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
If the anomaly can be corrected in the SL TAC, the production chain is run again (the Use Cases which are impacted)
### Assistant:
KEYWORD: If
VARIABLE: the production chain
CONDITION: is run again
NOT_RELEVANT: (the Use Cases which are impacted)
CAUSE_1: the anomaly can be corrected in the SL TAC
EFFECT_1: the production chain is run again
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
If the FTP server fails, an incident has to be reported to the SL TAC Service Manager
### Assistant:
KEYWORD: If
VARIABLE: an incident
CONDITION: has to be reported to the SL TAC Service Manager
CAUSE_1: the FTP server fails
EFFECT_1: an incident has to be reported to the SL TAC Service Manager
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Once it is repaired, the products are available to the users but with delayed time
### Assistant:
KEYWORD: Once
VARIABLE: the products
CONDITION: with delayed time
CAUSE_1: it is repaired
EFFECT_1: the products are available to the users
AND: but
EFFECT_2: with delayed time
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The requests may be addressed via different communication means (for example through a form), and processed by a dedicated service (Service Desk, at top level) and are cascaded to the SL TAC Service Desk in case of requested information about SL TAC
### Assistant:
KEYWORD: in case of
VARIABLE: The requests
CONDITION: are cascaded to the SL TAC Service Desk
CAUSE_1: requested information about SL TAC
AND: and
EFFECT_1: The requests may be addressed via different communication means
EFFECT_2: processed by a dedicated service
EFFECT_3: are cascaded to the SL TAC Service Desk
NOT_RELEVANT: (Service Desk, at top level)
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
There is not a one-to-one correspondence between the user stories and the “steps” of the cookbook because some steps were too complex to fit into a single coherent user story
### Assistant:
KEYWORD: because
VARIABLE: There
CONDITION: a one-to-one correspondence between the user stories and the “steps” of the cookbook
CAUSE_1: some steps were too complex to fit into a single coherent user story
NEGATION: is not
EFFECT_1: There is not a one-to-one correspondence between the user stories and the “steps” of the cookbook
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Because resources available to the DESSIN project do not allow for implementation of all of the user stories described in the document, it is also necessary to prioritize
### Assistant:
KEYWORD: Because
VARIABLE: it
CONDITION: available to the DESSIN project
CAUSE_1: resources available to the DESSIN project
EFFECT_1: it is also necessary to prioritize
NEGATION: do not
CAUSE_2: do not allow for implementation of all of the user stories described in the document
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Must: Stories labeled as “must” are stories that must be included in the Final solution
### Assistant:
NOT_RELEVANT: Must:
VARIABLE: stories
CONDITION: must be included in the Final solution
CAUSE_1: Stories labeled as “must”
EFFECT_1: stories
KEYWORD: are
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
All stories labeled as “must” will be implemented in the final version of the software tool (D23.2)
### Assistant:
VARIABLE: All stories
CONDITION: will be implemented in the final version of the software tool
CAUSE_1: All stories labeled as “must”
EFFECT_1: will be implemented in the final version of the software tool
NOT_RELEVANT: (D23.2)
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Should: Stories labeled as “should” are stories that should be included if possible
### Assistant:
NOT_RELEVANT: Should
VARIABLE: stories
CONDITION: possible
EFFECT_1: stories
CAUSE_1: Stories labeled as “should”
KEYWORD: are
CAUSE_2: possible
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
These stories are not essential for fulfilling the purpose of the software; however, not including them may force users to undertake time-consuming work-arounds
### Assistant:
CONDITION: to undertake time-consuming work-arounds
VARIABLE: users
NEGATION: not
CAUSE_1: not including them
EFFECT_1: may force users to undertake time-consuming work-arounds
NOT_RELEVANT: These stories are not essential for fulfilling the purpose of the software; however
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Here the relevant Drivers and Pressures are identified in order to understand the full picture of the system under study
### Assistant:
VARIABLE: the full picture of the system under study
AND: and
NOT_RELEVANT: Here
CONDITION: to understand
KEYWORD: in order
CAUSE_1: the relevant Drivers
CAUSE_2: Pressures are identified
EFFECT_1: to understand the full picture of the system under study
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
In specific cases where the proposed measures are expected/found to influence Pressures, then changes in those Pressures should be quantified
### Assistant:
KEYWORD: then
VARIABLE: changes in those Pressures
CONDITION: should be quantified
OR: /
CAUSE_1: the proposed measures are expected
CAUSE_2: found to influence Pressures
EFFECT_1: changes in those Pressures should be quantified
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
For each additional state parameter identified in 3.6, the user is provided with the full CICES list and prompted to select ESS classes affected by the additional state parameter
### Assistant:
VARIABLE: the user
CONDITION: prompted to select ESS classes affected by the additional state parameter
NOT_RELEVANT: For each
AND: and
CAUSE_1: additional state parameter identified in 3.6
EFFECT_1: the user is provided with the full CICES list
EFFECT_2: prompted to select ESS classes affected by the additional state parameter
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The list also includes the information provided in columns D, E and F in order to assist me with the selection
### Assistant:
VARIABLE: the selection
CONDITION: F
KEYWORD: in order
CAUSE_1: The list also includes the information provided in columns D,
EFFECT_1: to assist me with the selection
AND: and
CAUSE_2: E
CAUSE_3: F
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Data that is taken from the ESS Evaluation part should be marked in the table with an automatic reference provided
### Assistant:
VARIABLE: an automatic reference
CONDITION: provided
CAUSE_1: is taken from the ESS Evaluation part
EFFECT_1: should be marked in the table
KEYWORD: that
AND: with
EFFECT_2: an automatic reference provided
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
If the number is higher than 0, then cost coverage is guaranteed
### Assistant:
KEYWORD: then
VARIABLE: cost coverage
CONDITION: is guaranteed
CAUSE_1: the number is higher than 0
EFFECT_1: cost coverage is guaranteed
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
All indicator values are normalized automatically after the user defines if the highest or the lowest value is the best for each
### Assistant:
VARIABLE: the user
CONDITION: defines if the highest or the lowest value is the best for each
KEYWORD: after
EFFECT_1: All indicator values are normalized automatically
CAUSE_1: the user defines if the highest or the lowest value is the best for each
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
If the number is less than 1.0, then the cost- benefit analysis is negative
### Assistant:
KEYWORD: then
VARIABLE: the cost- benefit analysis
CONDITION: is negative
CAUSE_1: the number is less than 1.0
EFFECT_1: he cost- benefit analysis is negative
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
If it's greater than 1.0, then there's a positive return
### Assistant:
KEYWORD: then
VARIABLE: there
CONDITION: 's a positive return
CAUSE_1: it's greater than 1.0
EFFECT_1: there's a positive return
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Because the software requirements have been developed in close consultation with the developers of the ESS evaluation framework as well as the end user group, it is anticipated that the resulting software tool will be useful to the Demo site partners when they apply the DESSIN evaluation framework at their sites
### Assistant:
KEYWORD: e
VARIABLE: they
CONDITION: apply the DESSIN evaluation framework at their sites
AND: as well as
EFFECT_1: the resulting software tool will be useful to the Demo site partners
CAUSE_1: the software requirements have been developed in close consultation with the developers of the ESS evaluation framework
CAUSE_2: the end user group
CAUSE_3: they apply the DESSIN evaluation framework at their sites
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
In the event of conflict between the contents of the applicable documents and this document, the applicable documents shall take precedence
### Assistant:
KEYWORD: In the event of
VARIABLE: the applicable documents
CONDITION: between the contents of the applicable documents and this document
CAUSE_1: conflict between the contents of the applicable documents and this document
EFFECT_1: the applicable documents shall take precedence
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
In the event of conflict between the contents of the referenced documents and this document, this document shall take precedence
### Assistant:
KEYWORD: In the event of
VARIABLE: this document
CONDITION: between the contents of the referenced documents and this document
CAUSE_1: conflict between the contents of the referenced documents and this document
EFFECT_1: this document shall take precedence
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Making assumptions explicit and connecting them to an argued rationale enables decisions to be re‐ visited without starting all over again
### Assistant:
VARIABLE: decisions
CONDITION: starting all over again
AND: and
CAUSE_1: Making assumptions explicit
CAUSE_2: connecting them to an argued rationale
KEYWORD: enables
EFFECT_1: decisions to be re‐ visited
NEGATION: without
EFFECT_2: without starting all over again
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
An understanding of rationale enables accurate prioritisation and is an aid to preventing essential requirements from being deleted
### Assistant:
VARIABLE: essential requirements
CONDITION: from being deleted
CAUSE_1: An understanding of rationale
EFFECT_1: enables accurate prioritisation
AND: and
EFFECT_2: to preventing essential requirements from being deleted
KEYWORD: is an aid
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Changing the beam former weights shall be possible every 60 seconds (TBC) in the case of scheduled switching sequences
### Assistant:
VARIABLE: switching sequences
CONDITION: scheduled
KEYWORD: in the case of
EFFECT_1: Changing the beam former weights shall be possible every 60 seconds (TBC)
CAUSE_1: scheduled switching sequences
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Changing the beam former weights shall be possible within 60 seconds in case of changes due to manual interaction or changes in schedule
### Assistant:
VARIABLE: changes in schedule
CONDITION: due to manual interaction
KEYWORD: in case of
OR: or
EFFECT_1: Changing the beam former weights shall be possible within 60 seconds
CAUSE_1: changes due to manual interaction
CAUSE_2: changes in schedule
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The polarisation introduced by the calibration, shall be less than 0.5% of the total intensity
### Assistant:
VARIABLE: The polarisation
CONDITION: shall be less than 0.5% of the total intensity
CAUSE_1: The polarisation introduced by the calibration
EFFECT_1: shall be less than 0.5% of the total intensity
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
It shall be possible to abort an observation if monitor parameters exceed user specified limits (including RFI mitigation performance indication parameters)
### Assistant:
KEYWORD: if
VARIABLE: monitor parameters
CONDITION: exceed user specified limits
EFFECT_1: It shall be possible to abort an observation
CAUSE_1: monitor parameters exceed user specified limits
NOT_RELEVANT: (including RFI mitigation performance indication parameters)
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The control system shall be capable of autonomously calculating system settings in response to changes in instrument status, environment or measurement results
### Assistant:
KEYWORD: in response to
VARIABLE: The control system
OR: or
CONDITION: shall be capable of autonomously calculating system settings
CAUSE_1: changes in instrument status
CAUSE_2: environment
CAUSE_3: measurement results
EFFECT_1: The control system shall be capable of autonomously calculating system settings
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
If the normal measurement sequence does not provide for control verification in a timely fashion, such measurements shall be made out of sequence
### Assistant:
KEYWORD: If
VARIABLE: such measurements
CONDITION: shall be made out of sequence
CAUSE_1: the normal measurement sequence does not provide for control verification in a timely fashion
EFFECT_1: such measurements shall be made out of sequence
NEGATION: does not
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The absence of operator commands shall not cause catastrophic or serious consequences
### Assistant:
VARIABLE: serious consequences
CONDITION: The absence of
KEYWORD: cause
NEGATION: shall not
OR: or
CAUSE_1: The absence of operator commands
EFFECT_1: catastrophic
EFFECT_2: serious consequences
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
Failing equipment shall indicate the problem if power is on, and the control function shall take appropriate measures
### Assistant:
VARIABLE: the control function
CONDITION: shall take appropriate measures
KEYWORD: if
AND: and
EFFECT_1: Failing equipment shall indicate the problem
CAUSE_1: power is on
EFFECT_2: the control function shall take appropriate measures
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
SKA1 shall be able to recover autonomously in case of failures that are classified as minor or negligible
### Assistant:
VARIABLE: failures
CONDITION: negligible
KEYWORD: that
OR: or
CAUSE_2: negligible
CAUSE_1: are classified as minor
EFFECT_1: SKA1 shall be able to recover autonomously
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The average availability of SKA1 during the operational period shall be better than 90% (TBC)
### Assistant:
VARIABLE: the
KEYWORD: during
CONDITION: shall be better than 90% (TBC)
CAUSE_1: the operational period
EFFECT_1: shall be better than 90% (TBC).
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
This feature should be built into the final system unless its cost is too high
### Assistant:
NEGATION: unless
VARIABLE: This feature
CONDITION: should be built into the final system
CAUSE_1: its cost is too high
EFFECT_1: This feature should be built into the final system
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
This feature is recorded here so that the idea is not lost
### Assistant:
KEYWORD: so that
VARIABLE: the idea
CONDITION: lost
CAUSE_1: This feature is recorded here
EFFECT_1: the idea is not lost
NEGATION: is not
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The user interface contains logic to determine compatibility between components when loading / creating an Emulator Specification Document (ESD)
### Assistant:
VARIABLE: an Emulator Specification Document
CONDITION: creating
KEYWORD: when
OR: /
CAUSE_2: creating an Emulator Specification Document
CAUSE_1: loading
EFFECT_1: he user interface contains logic to determine compatibility between components
NOT_RELEVANT: (ESD)
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
However, this is not a mandatory requirement because it is assumed that computers will continue to become faster (based on Moore’s law)
### Assistant:
KEYWORD: because
NOT_RELEVANT: (based on Moore’s law)
VARIABLE: it
CONDITION: is assumed that computers will continue to become faster
EFFECT_1: this is not a mandatory requirement
CAUSE_1: it is assumed that computers will continue to become faster
NEGATION: is not
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
As this emulator will be focused on future use, speed is currently not an issue
### Assistant:
KEYWORD: As
VARIABLE: speed
CONDITION: an issue
CAUSE_1: this emulator will be focused on future use
EFFECT_1: speed is currently not an issue
NEGATION: not
### END
|
### Instruction:
Extract the cause and effect entities from the following sentence:
The RTGS account holder whose account is subject to the credit is not blocked
### Assistant:
VARIABLE: account
KEYWORD: whose
CONDITION: blocked
CAUSE_1: account is subject to the credit
EFFECT_1: is not blocked
NEGATION: is not
### END
|