Triple

T17992406
Position Surface form Disambiguated ID Type / Status
Subject Mūsa E430404 entity
Predicate locatedOn P40 FINISHED
Object European continent 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: European continent | Statement: [Mūsa, locatedOn, European continent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: European continent
Context triple: [Mūsa, locatedOn, European continent]
  • A. Continental Europe
    Continental Europe is the mainland portion of the European continent, excluding its surrounding islands such as Great Britain and Ireland.
  • B. Europa
    Europa is a figure in Greek mythology, a Phoenician princess famously abducted by Zeus and later the eponymous queen of Crete.
  • C. 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.
  • D. 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.
  • E. Europa chosen
    Europa is one of the traditional continents of the Earth, encompassing a diverse range of countries, cultures, and histories commonly referred to in English as Europe.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b2a0f8588190b6090c7cce60a35f completed April 19, 2026, 10:46 a.m.
Created at: April 10, 2026, 10:23 a.m.