Triple

T4153039
Position Surface form Disambiguated ID Type / Status
Subject Archbishop of Athens and All Greece E89950 entity
Predicate seat P75 FINISHED
Object Athens E12615 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: Athens | Statement: [Archbishop of Athens and All Greece, seat, Athens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Athens
Context triple: [Archbishop of Athens and All Greece, seat, Athens]
  • A. Athens chosen
    Athens is Greece’s largest city and a historic center of ancient civilization, renowned as the birthplace of democracy and Western philosophy.
  • B. 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.
  • C. Athens
    Athens is a small town in Mercer County, West Virginia, best known as the home of Concord University.
  • D. Athens
    Athens is a small city in northern Alabama known as the county seat of Limestone County and part of the Huntsville-Decatur metropolitan area.
  • E. Athens
    Athens is a small college town in southeastern Ohio best known as the home of Ohio University and its vibrant campus-centered community.
  • 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_69aed95a59a881909b26e70b42c6811a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0277a910819085cde5df9a8110d8 completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f15f0088190b2ec453183f0ca7f completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:44 p.m.