Triple

T19696985
Position Surface form Disambiguated ID Type / Status
Subject Korçë region E472985 entity
Predicate contains P35 FINISHED
Object Bilisht 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: Bilisht | Statement: [Korçë region, contains, Bilisht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bilisht
Context triple: [Korçë region, contains, Bilisht]
  • A. Bilisht chosen
    Bilisht is a small town in southeastern Albania near the Greek border, serving as an administrative and local commercial center for the surrounding rural area.
  • B. Leshem
    Leshem is an ancient Canaanite city in the northern Levant, later known as Laish and associated with the biblical tribe of Dan.
  • C. Bais City
    Bais City is a component city in Negros Oriental in the Central Visayas region of the Philippines, known for its sugar industry and dolphin- and whale-watching tourism.
  • D. Bentov
    Bentov is a Hebrew surname most notably associated with Mordechai Bentov, an Israeli politician and signatory of the Israeli Declaration of Independence.
  • E. Beshte
    Beshte is a friendly and strong hippopotamus who serves as the good-natured, powerful member of the Lion Guard in the Disney Junior series.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6421527b08190858788265043792d completed April 20, 2026, 3:11 p.m.
Created at: April 10, 2026, 1:46 p.m.