Triple

T18367214
Position Surface form Disambiguated ID Type / Status
Subject Selenological and Engineering Explorer E440078 entity
Predicate alsoKnownAs P39 FINISHED
Object SELENE
SELENE is a Japanese lunar orbiter mission designed to study the Moon’s origin, evolution, and surface characteristics using a suite of scientific instruments.
 E1321769 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: SELENE | Statement: [Selenological and Engineering Explorer, alsoKnownAs, SELENE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SELENE
Context triple: [Selenological and Engineering Explorer, alsoKnownAs, SELENE]
  • A. Luna
    Luna was an ancient Roman town in northern Italy that served as a key urban and commercial center for the Ligurian region.
  • B. Luna
    Luna is the protagonist of the game "Lunar: The Silver Star," a classic Japanese role-playing game known for its character-driven story and fantasy adventure.
  • C. Luna
    Luna is the intelligent, talking black cat who serves as a mentor and guide to Usagi Tsukino and the other Sailor Guardians in the Sailor Moon series.
  • D. Luna
    Luna is a Spanish surname most prominently associated with Mexican actor and filmmaker Diego Luna.
  • E. Luna
    Luna is the gentle, talking moon character who serves as a wise, comforting friend and advisor to Bear in the children's television series "Bear in the Big Blue House."
  • 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: SELENE
Triple: [Selenological and Engineering Explorer, alsoKnownAs, SELENE]
Generated description
SELENE is a Japanese lunar orbiter mission designed to study the Moon’s origin, evolution, and surface characteristics using a suite of scientific instruments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SELENE
Target entity description: SELENE is a Japanese lunar orbiter mission designed to study the Moon’s origin, evolution, and surface characteristics using a suite of scientific instruments.
  • A. Luna
    Luna is the natural satellite of Earth, renowned for its phases, influence on tides, and prominence in human culture and mythology.
  • B. Luna
    Luna was an ancient Roman town in northern Italy that served as a key urban and commercial center for the Ligurian region.
  • C. Luna
    Luna is a Spanish surname most prominently associated with Mexican actor and filmmaker Diego Luna.
  • D. Luna
    Luna is the protagonist of the game "Lunar: The Silver Star," a classic Japanese role-playing game known for its character-driven story and fantasy adventure.
  • E. Luna
    Luna is the live wolf mascot that represents the University of Nevada's Wolf Pack football program.
  • 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5174f5f448190a1fc67d3039aadd9 completed April 19, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03d7764a84819095e35108a71f8e96 completed May 13, 2026, 1:44 a.m.
NEDg Description generation batch_6a03de5ba068819080dfdf66ba03eb5c completed May 13, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_6a03defaf90c81908348ebd286de0e32 completed May 13, 2026, 2:16 a.m.
Created at: April 10, 2026, 10:38 a.m.