Triple

T20801575
Position Surface form Disambiguated ID Type / Status
Subject Toesca metro station E512052 entity
Predicate locatedInNeighborhood P40 FINISHED
Object Toesca NE NERFINISHED

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: Toesca | Statement: [Toesca metro station, locatedInNeighborhood, Toesca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toesca
Context triple: [Toesca metro station, locatedInNeighborhood, Toesca]
  • A. Toesca chosen
    Toesca is an Italian-origin surname best known through Joaquín Toesca, an 18th-century architect influential in colonial Chilean architecture.
  • B. Monasca
    Monasca is an OpenStack project that provides a scalable, multi-tenant monitoring-as-a-service solution for metrics, logs, and alarms in cloud environments.
  • C. Mesos
    Mesos is an open-source cluster manager that abstracts CPU, memory, and other resources across distributed systems to efficiently run and scale applications and frameworks.
  • D. Tirora
    Tirora is a town in the Gondia district of Maharashtra, India, known for its agricultural surroundings and regional commercial activity.
  • E. Tekton
    Tekton is an open-source framework for building cloud-native CI/CD systems on Kubernetes using reusable, declarative pipelines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4cc69f481908e98751e697b9df4 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2b0d75881909cc89ebe4e27adc1 completed April 21, 2026, 12:20 a.m.
Created at: April 16, 2026, 12:39 p.m.