Triple

T17773321
Position Surface form Disambiguated ID Type / Status
Subject Athina Onassis E443696 entity
Predicate givenName P17 FINISHED
Object Athina 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: Athina | Statement: [Athina Onassis, givenName, Athina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Athina
Context triple: [Athina Onassis, givenName, Athina]
  • A. Athina chosen
    Athina is the given name of Athina Onassis, the granddaughter and principal heir of Greek shipping magnate Aristotle Onassis.
  • B. Atina
    Atina is a historic hill town in Italy’s Lazio region, known for its medieval architecture and scenic position in the Comino Valley.
  • C. Athens
    Athens is Greece’s largest city and a historic center of ancient civilization, renowned as the birthplace of democracy and Western philosophy.
  • D. Athens
    Athens is a historic college town in northeastern Georgia, best known as the home of the University of Georgia and for its vibrant music and arts scene.
  • E. Athens
    Athens is a small town in Mercer County, West Virginia, best known as the home of Concord University.
  • 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871a2130819081743ae89dddc64b completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:12 a.m.