Triple

T5074477
Position Surface form Disambiguated ID Type / Status
Subject Maribor E114358 entity
Predicate hasTwinTown P919 FINISHED
Object Ploiești, Romania E277709 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: Ploiești, Romania | Statement: [Maribor, hasTwinTown, Ploiești, Romania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ploiești, Romania
Context triple: [Maribor, hasTwinTown, Ploiești, Romania]
  • A. Ploiești, Romania
    Ploiești is a major Romanian city in Prahova County, historically known for its oil industry and refineries that made it a key European petroleum center.
  • B. Ploiești chosen
    Ploiești is a major city in southern Romania historically known for its oil industry and strategic importance during World War II.
  • C. Sibiu, Romania
    Sibiu, Romania is a historic Transylvanian city known for its well-preserved medieval architecture and cultural significance, including being named a European Capital of Culture in 2007.
  • D. Pitești
    Pitești is a city in southern Romania, known as an important industrial and transportation hub and the capital of Argeș County.
  • E. Galați
    Galați is a major Romanian port city in eastern Romania, situated near the border with Moldova and known for its shipbuilding and steel industries.
  • 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_69bd443cf28c8190ad371d603563dbdd completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74d0be1c819081b26235fe602a30 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb11b3f3c819089f09178f17940c5 completed March 21, 2026, 2:54 p.m.
Created at: March 20, 2026, 1:39 p.m.