Triple

T4786682
Position Surface form Disambiguated ID Type / Status
Subject Yerevan E106494 entity
Predicate hasSisterCity P919 FINISHED
Object Chișinău E134770 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: Chișinău | Statement: [Yerevan, hasSisterCity, Chișinău]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chișinău
Context triple: [Yerevan, hasSisterCity, Chișinău]
  • A. Chișinău chosen
    Chișinău is the largest city and main political, economic, and cultural center of Moldova.
  • B. Tiraspol
    Tiraspol is the de facto capital and largest city of the unrecognized breakaway region of Transnistria in eastern Moldova.
  • C. Iași
    Iași is a major cultural, academic, and economic center in northeastern Romania, known for its historic universities, churches, and role as a former capital of the Principality of Moldavia.
  • D. Beltsy, Moldova
    Beltsy, Moldova is a major industrial and cultural city in northern Moldova, often considered the country’s second-largest urban center.
  • E. Bucharest
    Bucharest is the capital and largest city of Romania, known for its mix of historic architecture, wide boulevards, and its role as the country’s political, cultural, and economic center.
  • 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_69bd43f4a9588190bf73e20bc27c03cc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd65d8f9d881909c24340b8dc6a104 completed March 20, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be43e01f6c81909ca0121c36d107e9 completed March 21, 2026, 7:08 a.m.
Created at: March 20, 2026, 1:22 p.m.