Triple

T4744240
Position Surface form Disambiguated ID Type / Status
Subject Chalkidiki (regional unit) E105320 entity
Predicate hasCity P316 FINISHED
Object Nikiti E234949 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: Nikiti | Statement: [Chalkidiki (regional unit), hasCity, Nikiti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nikiti
Context triple: [Chalkidiki (regional unit), hasCity, Nikiti]
  • A. Nikiti chosen
    Nikiti is a coastal town and popular tourist resort on the Sithonia peninsula in northern Greece’s Chalkidiki region.
  • B. Koropi
    Koropi is a town in the Athens metropolitan area of Greece, known as the seat of the municipality of Kropia and a local hub in the Mesogeia plain.
  • C. Nikolassee
    Nikolassee is a residential locality in southwestern Berlin known for its lakeside setting, green spaces, and villa-style neighborhoods.
  • D. Nisaea
    Nisaea was the port town and harbor of ancient Megara in Greece, serving as its main maritime outlet on the Saronic Gulf.
  • E. Karpenisi
    Karpenisi is a small mountainous town in central Greece known for its scenic landscapes, winter sports, and traditional Greek character.
  • 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_69bd43ef87a48190a5bc3600711aa032 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64aa72c0819082ede0f531d75e65 completed March 20, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a37a77881909d32027f1ada99c5 completed March 21, 2026, 6:27 a.m.
Created at: March 20, 2026, 1:19 p.m.