Triple

T22751673
Position Surface form Disambiguated ID Type / Status
Subject Chamberí E562716 entity
Predicate borderedByDistrict P224 FINISHED
Object Centro 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: Centro | Statement: [Chamberí, borderedByDistrict, Centro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Centro
Context triple: [Chamberí, borderedByDistrict, Centro]
  • A. Centro
    Centro is a NUTS 2 statistical region in central Portugal that includes areas such as Aveiro and Coimbra.
  • B. Centro
    Centro is a municipality in the Mexican state of Tabasco whose administrative center is the city of Villahermosa.
  • C. Centro
    Centro is the central urban district and main commercial hub of Novo Hamburgo in Rio Grande do Sul, Brazil.
  • D. Centro
    Centro was the former public transport authority for the West Midlands metropolitan area in England, responsible for coordinating local bus, rail, and tram services before being succeeded by Transport for West Midlands.
  • E. Centro chosen
    Centro is Madrid’s historic central district, known for landmarks like Puerta del Sol and Plaza Mayor and its role as the city’s main cultural and commercial hub.
  • 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_69e24551ec7881909a9c924dbea155f6 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f179b9ac348190bff4dc470931f7e3 completed April 29, 2026, 3:23 a.m.
Created at: April 17, 2026, 3:24 p.m.