Triple

T15868930
Position Surface form Disambiguated ID Type / Status
Subject Sector 1, Bucharest E384782 entity
Predicate containsPart P35 FINISHED
Object Băneasa E629485 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: Băneasa | Statement: [Sector 1, Bucharest, containsPart, Băneasa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Băneasa
Context triple: [Sector 1, Bucharest, containsPart, Băneasa]
  • A. Băneasa chosen
    Băneasa is a northern district of Bucharest, Romania, known for its residential areas, shopping centers, and proximity to Băneasa Airport and Băneasa Forest.
  • B. Băneasa
    Băneasa is a commune in southeastern Romania, located in Constanța County near the border with Bulgaria.
  • C. Rochor
    Rochor is a central urban planning area and historic district in Singapore known for its mix of heritage sites, commercial activity, and dense public housing.
  • D. Petrești
    Petrești is a village that forms part of the town of Sebeș in Alba County, central Romania.
  • E. Buzău
    Buzău is a city in southeastern Romania, serving as the capital of Buzău County and an important regional economic and cultural center.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155f7fe8c81908fb60ada27b14c8b completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa94a4d208190805d33da0e433092 completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:50 a.m.