Triple

T1790517
Position Surface form Disambiguated ID Type / Status
Subject The Martian E39484 entity
Predicate mainCharacter P1183 FINISHED
Object Mark Watney
Mark Watney is the resourceful astronaut and botanist who becomes stranded alone on Mars and must use his ingenuity to survive in Andy Weir’s science fiction novel "The Martian."
E197785 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: Mark Watney | Statement: [The Martian, mainCharacter, Mark Watney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Watney
Context triple: [The Martian, mainCharacter, Mark Watney]
  • A. Matt Kowalski
    Matt Kowalski is a veteran NASA astronaut and spacewalker featured as a central character in the science fiction film "Gravity."
  • B. Dr. Ryan Stone
    Dr. Ryan Stone is the rookie medical engineer and astronaut portrayed by Sandra Bullock in the space survival film "Gravity."
  • C. Fred Haise
    Fred Haise is an American astronaut and test pilot best known as the lunar module pilot on the ill-fated Apollo 13 mission.
  • D. Jack Swigert
    Jack Swigert was an American astronaut, test pilot, and politician best known as the command module pilot of NASA’s ill-fated Apollo 13 lunar mission.
  • E. Greg Grissom
    Greg Grissom is a sports executive who serves as the president of the NFL’s Houston Texans franchise.
  • 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: Mark Watney
Triple: [The Martian, mainCharacter, Mark Watney]
Generated description
Mark Watney is the resourceful astronaut and botanist who becomes stranded alone on Mars and must use his ingenuity to survive in Andy Weir’s science fiction novel "The Martian."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mark Watney
Target entity description: Mark Watney is the resourceful astronaut and botanist who becomes stranded alone on Mars and must use his ingenuity to survive in Andy Weir’s science fiction novel "The Martian."
  • A. Matt Kowalski
    Matt Kowalski is a veteran NASA astronaut and spacewalker featured as a central character in the science fiction film "Gravity."
  • B. Dr. Ryan Stone
    Dr. Ryan Stone is the rookie medical engineer and astronaut portrayed by Sandra Bullock in the space survival film "Gravity."
  • C. Fred Haise
    Fred Haise is an American astronaut and test pilot best known as the lunar module pilot on the ill-fated Apollo 13 mission.
  • D. Jack Swigert
    Jack Swigert was an American astronaut, test pilot, and politician best known as the command module pilot of NASA’s ill-fated Apollo 13 lunar mission.
  • E. Greg Grissom
    Greg Grissom is a sports executive who serves as the president of the NFL’s Houston Texans franchise.
  • 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_69a88631854081909723959921e45c2b completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6512804c8190a5743c10bd37f83f completed March 6, 2026, 5:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada9aa10b881909923b8d0f3a30ee6 completed March 8, 2026, 4:54 p.m.
NEDg Description generation batch_69adab05cf6c81909f4713664f508ad9 completed March 8, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69adaeb31430819083d033a3890eba49 completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:32 p.m.