Triple

T19506296
Position Surface form Disambiguated ID Type / Status
Subject DN73 E488029 entity
Predicate connectsCities P4245 FINISHED
Object Câmpulung 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: Câmpulung | Statement: [DN73, connectsCities, Câmpulung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Câmpulung
Context triple: [DN73, connectsCities, Câmpulung]
  • A. Câmpulung chosen
    Câmpulung is a historic town in southern Romania, known as one of the country’s oldest urban settlements and an early medieval capital of Wallachia.
  • B. Comănești
    Comănești is a town in Bacău County, Romania, known for its location in the Trotuș Valley and its historical role in the region’s timber and coal industries.
  • C. Bălcești
    Bălcești is a small town in Vâlcea County, Romania, situated in the historical region of Oltenia.
  • D. Tărlungeni
    Tărlungeni is a commune in Brașov County, Romania, known for its rural character and proximity to the city of Brașov in the historical region of Transylvania.
  • E. Giulești
    Giulești is a residential neighborhood in western Bucharest, Romania, known for its working-class character and association with the Rapid București football club.
  • 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63511fc688190bd1474406060fa1b completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.