Triple

T7283142
Position Surface form Disambiguated ID Type / Status
Subject Congo Airways E163798 entity
Predicate cityServed P82 FINISHED
Object Lubero E468939 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: Lubero | Statement: [Congo Airways, cityServed, Lubero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lubero
Context triple: [Congo Airways, cityServed, Lubero]
  • A. Lubero chosen
    Lubero is a town and administrative center located in the mountainous region of North Kivu in the eastern Democratic Republic of the Congo.
  • B. Lamboya
    Lamboya is an Austronesian language spoken by the Lamboya people on the island of Sumba in eastern Indonesia.
  • C. Forlani
    Forlani is an Italian surname most notably associated with English actress Claire Forlani.
  • D. Lugana
    Lugana is an Italian white wine appellation near Lake Garda, renowned for its fresh, mineral-driven wines primarily made from the Turbiana grape.
  • E. Rauco
    Rauco is a rural municipality and commune in central Chile’s Maule Region, known for its agricultural activities and proximity to the city of Curicó.
  • 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_69c6886093b88190a254b1ce6db8bae7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb4ec2088190a6713eaa221d49a6 completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db3ae6a08190820c7096cbfea521 completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:59 p.m.