Triple

T8109679
Position Surface form Disambiguated ID Type / Status
Subject Ploiești E189315 entity
Predicate near P350 FINISHED
Object Bucharest E31636 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: Bucharest | Statement: [Ploiești, near, Bucharest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bucharest
Context triple: [Ploiești, near, Bucharest]
  • A. Bucharest chosen
    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.
  • B. Cluj-Napoca
    Cluj-Napoca is a major city in northwestern Romania, known as a cultural, academic, and economic hub of the Transylvania region.
  • C. Craiova
    Craiova is a major city in southwestern Romania, known as an important economic, cultural, and university center of the historical region of Oltenia.
  • D. Timișoara
    Timișoara is a major city in western Romania known for its historical architecture, multicultural heritage, and role as a key economic and cultural center.
  • E. Otopeni
    Otopeni is a town in Ilfov County, Romania, just north of Bucharest, best known for hosting the country’s main international airport.
  • 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_69ca82b9d5848190a24672775d5c5011 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42fbc57c81908c6be87bbc547085 completed March 31, 2026, 3:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc937366b8819091f08f8f7facf6f6 completed April 1, 2026, 3:39 a.m.
Created at: March 30, 2026, 5:32 p.m.