Triple

T3740899
Position Surface form Disambiguated ID Type / Status
Subject Galileo spacecraft E79694 entity
Predicate target P860 FINISHED
Object Europa E126262 NE FINISHED

How this triple was built (2 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: Europa | Statement: [Galileo spacecraft, target, Europa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europa
Context triple: [Galileo spacecraft, target, Europa]
  • A. Europa chosen
    Europa is one of Jupiter’s large icy moons, notable for its smooth frozen surface and the subsurface ocean that makes it a prime candidate in the search for extraterrestrial life.
  • B. Europa
    Europa is a European-themed section of the Worlds of Fun amusement park in Kansas City, Missouri, featuring attractions, architecture, and cuisine inspired by various European countries.
  • C. Europa
    Europa is a figure in Greek mythology, a Phoenician princess famously abducted by Zeus and later the eponymous queen of Crete.
  • D. Europe
    Europe is a diverse continent in the Northern Hemisphere known for its rich history, cultural heritage, and significant influence on global politics, economics, and science.
  • E. Eurasia
    Eurasia is the vast combined continental landmass of Europe and Asia, forming the largest continuous land area on Earth.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb549490819084ebe69aae5ccf95 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4fce13c8190bedd5c2afe93567c completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:34 p.m.