Triple

T747354
Position Surface form Disambiguated ID Type / Status
Subject Goddard Space Flight Center E15372 entity
Predicate manages P86 FINISHED
Object Goddard Earth Observing System models
The Goddard Earth Observing System models are a suite of advanced atmospheric and Earth system models used for global weather, climate, and data assimilation research and forecasting.
E88904 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Goddard Earth Observing System models | Statement: [Goddard Space Flight Center, manages, Goddard Earth Observing System models]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Goddard Earth Observing System models
Context triple: [Goddard Space Flight Center, manages, Goddard Earth Observing System models]
  • A. Global Data-processing and Forecasting System
    The Global Data-processing and Forecasting System is an international meteorological infrastructure that collects, processes, and distributes weather and climate data to support global forecasting and early warning services.
  • B. Global Climate Observing System
    The Global Climate Observing System is an international program that coordinates and supports comprehensive, long-term observations of the Earth’s climate system to underpin climate research, services, and policy.
  • C. Deep Space Climate Observatory
    The Deep Space Climate Observatory (DSCOVR) is a NOAA and NASA satellite positioned at the Sun–Earth L1 Lagrange point that continuously monitors solar wind conditions and provides real-time space weather and Earth observation data.
  • D. Mars Science Laboratory entry, descent, and landing modeling
    Mars Science Laboratory entry, descent, and landing modeling is the suite of analytical and computational tools used to predict and optimize the Curiosity rover’s atmospheric entry, parachute descent, and landing performance on Mars.
  • E. Geostationary Operational Environmental Satellite program
    The Geostationary Operational Environmental Satellite (GOES) program is a series of U.S. weather satellites in geostationary orbit that provide continuous monitoring of atmospheric, oceanic, and environmental conditions for forecasting and research.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Goddard Earth Observing System models
Triple: [Goddard Space Flight Center, manages, Goddard Earth Observing System models]
Generated description
The Goddard Earth Observing System models are a suite of advanced atmospheric and Earth system models used for global weather, climate, and data assimilation research and forecasting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Goddard Earth Observing System models
Target entity description: The Goddard Earth Observing System models are a suite of advanced atmospheric and Earth system models used for global weather, climate, and data assimilation research and forecasting.
  • A. Global Data-processing and Forecasting System
    The Global Data-processing and Forecasting System is an international meteorological infrastructure that collects, processes, and distributes weather and climate data to support global forecasting and early warning services.
  • B. Global Climate Observing System
    The Global Climate Observing System is an international program that coordinates and supports comprehensive, long-term observations of the Earth’s climate system to underpin climate research, services, and policy.
  • C. Deep Space Climate Observatory
    The Deep Space Climate Observatory (DSCOVR) is a NOAA and NASA satellite positioned at the Sun–Earth L1 Lagrange point that continuously monitors solar wind conditions and provides real-time space weather and Earth observation data.
  • D. Mars Science Laboratory entry, descent, and landing modeling
    Mars Science Laboratory entry, descent, and landing modeling is the suite of analytical and computational tools used to predict and optimize the Curiosity rover’s atmospheric entry, parachute descent, and landing performance on Mars.
  • E. Geostationary Operational Environmental Satellite program
    The Geostationary Operational Environmental Satellite (GOES) program is a series of U.S. weather satellites in geostationary orbit that provide continuous monitoring of atmospheric, oceanic, and environmental conditions for forecasting and research.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a62dd1bc819094a3814654448ae3 completed March 1, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654e664e4819081badaf0ba0d86e5 completed March 3, 2026, 3:26 a.m.
NEDg Description generation batch_69a655e0a2608190801fb67856bc2ac4 completed March 3, 2026, 3:30 a.m.
NED2 Entity disambiguation (via description) batch_69a65704a964819097ad5074e83303b4 completed March 3, 2026, 3:35 a.m.
Created at: March 1, 2026, 7:37 p.m.