Triple

T20935109
Position Surface form Disambiguated ID Type / Status
Subject Damno E515563 entity
Predicate hasChild P369 FINISHED
Object Europa NE NERFINISHED

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: [Damno, hasChild, Europa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europa
Context triple: [Damno, hasChild, Europa]
  • A. Europa
    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 1991 surreal, noir-style drama film by Danish director Lars von Trier, known for its striking visual style and hypnotic narrative set in post-World War II Germany.
  • D. Europa chosen
    Europa is a figure in Greek mythology, a Phoenician princess famously abducted by Zeus and later the eponymous queen of Crete.
  • E. Europa
    Europa is the primary continent-spanning, pseudo-European steampunk world in the Girl Genius webcomic, filled with mad science, clanking constructs, and warring powers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4fc13408190b06868df03c5c29b completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f950d5e081908ec0df4824cf69f7 completed April 21, 2026, 4:13 a.m.
Created at: April 16, 2026, 12:49 p.m.