Triple

T12506575
Position Surface form Disambiguated ID Type / Status
Subject Alba County E298962 entity
Predicate hasCity P316 FINISHED
Object Sebeș E290242 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: Sebeș | Statement: [Alba County, hasCity, Sebeș]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sebeș
Context triple: [Alba County, hasCity, Sebeș]
  • A. Sebeș chosen
    Sebeș is a historic town in central Romania’s Transylvania region, notable as an important medieval center of the Transylvanian Saxon community.
  • B. Berbești
    Berbești is a small town in south-central Romania known for its role in the regional mining and energy industry within Vâlcea County.
  • C. Beiuș
    Beiuș is a small historic town in western Romania’s Bihor County, known for its traditional architecture and role as a local cultural and educational center in the Crișana region.
  • D. Bălcești
    Bălcești is a small town in Vâlcea County, Romania, situated in the historical region of Oltenia.
  • E. Reșița
    Reșița is an industrial city in western Romania, historically known as a major center of steel production and engineering in the Banat region.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541ace208190a5149b6f18fa196d completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bb778e081909bab2ef87226c6a0 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.