Triple

T14472367
Position Surface form Disambiguated ID Type / Status
Subject Curtea de Argeș E358875 entity
Predicate nearbyCity P350 FINISHED
Object Pitești E113270 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: Pitești | Statement: [Curtea de Argeș, nearbyCity, Pitești]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pitești
Context triple: [Curtea de Argeș, nearbyCity, Pitești]
  • A. Pitești chosen
    Pitești is a city in southern Romania, known as an important industrial and transportation hub and the capital of Argeș County.
  • B. Băilești
    Băilești is a town in southwestern Romania, in Dolj County, known as a local agricultural and commercial center.
  • C. Ploiești
    Ploiești is a major city in southern Romania historically known for its oil industry and strategic importance during World War II.
  • D. Hârșova
    Hârșova is a small town in southeastern Romania, situated on the right bank of the Danube River and known for its historical and archaeological significance.
  • E. Râmnicu Vâlcea
    Râmnicu Vâlcea is a city in south-central Romania, located on the Olt River and serving as the capital of Vâlcea County.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91fab21c819090b6e209d8efba6e completed April 14, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff36455f788190a63507ecda42b04c completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 1:20 a.m.