Triple
T12542612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emily Lakdawalla |
E299879
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job
*The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job* is a detailed non-fiction book that explains the technology, design decisions, and operational challenges behind NASA’s Curiosity Mars rover for a general science audience.
|
E990143
|
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: The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job | Statement: [Emily Lakdawalla, notableWork, The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job Context triple: [Emily Lakdawalla, notableWork, The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job]
-
A.
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.
-
B.
Methane Sensor for Mars
Methane Sensor for Mars is a scientific instrument aboard India’s Mars Orbiter Mission designed to detect and measure methane in the Martian atmosphere.
-
C.
Sample Analysis at Mars
Sample Analysis at Mars is a suite of scientific instruments on NASA's Curiosity rover designed to analyze the chemistry and mineralogy of Martian rocks, soil, and atmosphere.
-
D.
Fast, cheap and out of control: A robot invasion of the solar system
"Fast, cheap and out of control: A robot invasion of the solar system" is an influential essay by roboticist Rodney Brooks advocating for swarms of small, inexpensive, autonomous robots as a practical strategy for space exploration.
-
E.
Compact Reconnaissance Imaging Spectrometer for Mars
The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is a high-resolution imaging spectrometer aboard NASA’s Mars Reconnaissance Orbiter designed to map the planet’s mineralogy and detect signs of past water activity.
- 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: The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job Triple: [Emily Lakdawalla, notableWork, The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job]
Generated description
*The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job* is a detailed non-fiction book that explains the technology, design decisions, and operational challenges behind NASA’s Curiosity Mars rover for a general science audience.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job Target entity description: *The Design and Engineering of Curiosity: How the Mars Rover Performs Its Job* is a detailed non-fiction book that explains the technology, design decisions, and operational challenges behind NASA’s Curiosity Mars rover for a general science audience.
-
A.
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.
-
B.
Methane Sensor for Mars
Methane Sensor for Mars is a scientific instrument aboard India’s Mars Orbiter Mission designed to detect and measure methane in the Martian atmosphere.
-
C.
Sample Analysis at Mars
Sample Analysis at Mars is a suite of scientific instruments on NASA's Curiosity rover designed to analyze the chemistry and mineralogy of Martian rocks, soil, and atmosphere.
-
D.
Fast, cheap and out of control: A robot invasion of the solar system
"Fast, cheap and out of control: A robot invasion of the solar system" is an influential essay by roboticist Rodney Brooks advocating for swarms of small, inexpensive, autonomous robots as a practical strategy for space exploration.
-
E.
Compact Reconnaissance Imaging Spectrometer for Mars
The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is a high-resolution imaging spectrometer aboard NASA’s Mars Reconnaissance Orbiter designed to map the planet’s mineralogy and detect signs of past water activity.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9547d6df4819080db8415d386ed38 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6557e6d4c81909ed54a039e92a160 |
completed | May 2, 2026, 7:50 p.m. |
| NEDg | Description generation | batch_69f6566f40c08190baec227fb660c948 |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f65799ca588190b9f7a07f5c1a842c |
completed | May 2, 2026, 7:59 p.m. |
Created at: April 8, 2026, 9:57 p.m.