Triple

T12934397
Position Surface form Disambiguated ID Type / Status
Subject Βίτσι E309466 entity
Predicate locatedNear P294 FINISHED
Object Florina E109166 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: Florina | Statement: [Βίτσι, locatedNear, Florina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florina
Context triple: [Βίτσι, locatedNear, Florina]
  • A. Florina chosen
    Florina is a town in northern Greece known for its mountainous landscape, cold winters, and role as a regional cultural and administrative center.
  • B. Litochoro
    Litochoro is a Greek town situated at the foot of Mount Olympus, known as a popular base for hiking and exploring the surrounding national park.
  • C. Arachova
    Arachova is a picturesque mountain town in central Greece, known for its traditional stone architecture, ski resort, and proximity to the ancient site of Delphi.
  • D. Vlahi
    Vlahi are an ethnographic group in Istria who identify as Vlachs, a Romance-speaking people historically spread across parts of the Balkans.
  • E. Konitsa
    Konitsa is a town in northwestern Greece known for its mountainous landscape, traditional stone architecture, and proximity to the Albanian border.
  • 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_69d7bdfa933c8190b5a27aa4a08a19b7 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97dc6517481908637781da240b51f completed April 10, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af6d16388190abc848ac67bf1fb9 completed May 3, 2026, 2:14 a.m.
Created at: April 9, 2026, 5:42 p.m.