Triple

T13097992
Position Surface form Disambiguated ID Type / Status
Subject Rio Metro Regional Transit District E310639 entity
Predicate providesServiceTo P82 FINISHED
Object Belen E755437 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: Belen | Statement: [Rio Metro Regional Transit District, providesServiceTo, Belen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belen
Context triple: [Rio Metro Regional Transit District, providesServiceTo, Belen]
  • A. Belen chosen
    Belen is a small city in central New Mexico known as a regional transportation hub and bedroom community for the Albuquerque metropolitan area.
  • B. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • C. Gracia
    Gracia is a feminine given name, commonly used in Spanish and other Romance languages, that derives from and shares the meaning of the name Grace.
  • D. Belmonte
    Belmonte is a historic town in Portugal known for its medieval castle and strong Jewish heritage, located in the country's Centro Region.
  • E. Mariental
    Mariental is a town in central Namibia that serves as an important agricultural and transport hub in the Hardap 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d981500d34819097037b3c3c33627b completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d619b82c819093d0d98db88eb9ae completed May 3, 2026, 4:59 a.m.
Created at: April 9, 2026, 9:04 p.m.