Triple

T12825998
Position Surface form Disambiguated ID Type / Status
Subject ArgoMoon E306652 entity
Predicate relatedMission P36268 FINISHED
Object LunIR
LunIR is a small NASA CubeSat mission designed to perform lunar flyby observations and demonstrate advanced miniaturized space technologies.
 E1004472 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: LunIR | Statement: [ArgoMoon, relatedMission, LunIR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LunIR
Context triple: [ArgoMoon, relatedMission, LunIR]
  • A. Lunan
    Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
  • B. Lunice
    Lunice is a Canadian electronic music producer and DJ known for his innovative trap-influenced beats and as one half of the duo TNGHT.
  • C. LUN
    LUN is the IATA airport code for Kenneth Kaunda International Airport, the main international gateway serving Lusaka, the capital city of Zambia.
  • D. Lunay
    Lunay is a Puerto Rican reggaeton and Latin trap singer known for hits like "Soltera" and collaborations with major urban Latin artists.
  • E. Lurk
    Lurk is a highly acclaimed Chinese espionage television drama series known for its intricate plotting and nuanced portrayal of undercover agents during the Chinese Civil War era.
  • 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: LunIR
Triple: [ArgoMoon, relatedMission, LunIR]
Generated description
LunIR is a small NASA CubeSat mission designed to perform lunar flyby observations and demonstrate advanced miniaturized space technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LunIR
Target entity description: LunIR is a small NASA CubeSat mission designed to perform lunar flyby observations and demonstrate advanced miniaturized space technologies.
  • A. Lunan
    Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
  • B. Lunice
    Lunice is a Canadian electronic music producer and DJ known for his innovative trap-influenced beats and as one half of the duo TNGHT.
  • C. LUN
    LUN is the IATA airport code for Kenneth Kaunda International Airport, the main international gateway serving Lusaka, the capital city of Zambia.
  • D. Lunay
    Lunay is a Puerto Rican reggaeton and Latin trap singer known for hits like "Soltera" and collaborations with major urban Latin artists.
  • E. Lurk
    Lurk is a highly acclaimed Chinese espionage television drama series known for its intricate plotting and nuanced portrayal of undercover agents during the Chinese Civil War era.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96facb2d48190bc12efc00c9da360 completed April 10, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ed4f7388190ba989b8a79bd7c6d completed May 2, 2026, 11:55 p.m.
NEDg Description generation batch_69f691341d0081909ca3b281ee64b42b completed May 3, 2026, 12:05 a.m.
NED2 Entity disambiguation (via description) batch_69f692361c3c81909078a19be1a86231 completed May 3, 2026, 12:09 a.m.
Created at: April 9, 2026, 5:33 p.m.