Triple

T18714423
Position Surface form Disambiguated ID Type / Status
Subject Терек E457597 entity
Predicate passesNear P416 FINISHED
Object Владикавказ 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: Владикавказ | Statement: [Терек, passesNear, Владикавказ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Владикавказ
Context triple: [Терек, passesNear, Владикавказ]
  • A. Vladikavkaz chosen
    Vladikavkaz is a major city in the North Caucasus region of Russia, serving as the capital of the Republic of North Ossetia–Alania and an important cultural and industrial center.
  • B. Grozny
    Grozny is the capital and largest city of the Chechen Republic in southwestern Russia, known for its turbulent recent history and extensive post-war reconstruction.
  • C. Stavropol
    Stavropol is a major administrative, cultural, and economic center in southwestern Russia, serving as the capital of Stavropol Krai in the North Caucasus region.
  • D. Makhachkala
    Makhachkala is the largest city and main political, economic, and cultural center of the Russian republic of Dagestan, located on the western shore of the Caspian Sea.
  • E. Krasnodar
    Krasnodar is a major city in southern Russia, serving as the administrative center of Krasnodar Krai and an important economic and cultural hub of the region.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56ab4ee6881908f19558937cbb078 completed April 19, 2026, 11:52 p.m.
Created at: April 10, 2026, 11:50 a.m.