Triple

T5336721
Position Surface form Disambiguated ID Type / Status
Subject Telephassa E123844 entity
Predicate child P120 FINISHED
Object Europa E62752 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: [Telephassa, child, Europa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europa
Context triple: [Telephassa, child, 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 chosen
    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. Europos
    Europos is an ancient city historically known as Rayy (or Rey), located near modern-day Tehran in Iran and recognized as one of the oldest continuously inhabited settlements in the region.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85b104c081908b81236a0142e1c8 completed March 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3a8f29488190b7c622a260319328 completed March 22, 2026, 12:40 a.m.
Created at: March 20, 2026, 2 p.m.