Triple

T6285146
Position Surface form Disambiguated ID Type / Status
Subject Estadio Vicente Calderón E140881 entity
Predicate locatedIn P40 FINISHED
Object Arganzuela district E533339 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: Arganzuela district | Statement: [Estadio Vicente Calderón, locatedIn, Arganzuela district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arganzuela district
Context triple: [Estadio Vicente Calderón, locatedIn, Arganzuela district]
  • A. Arganzuela district chosen
    Arganzuela district is a central district of Madrid, Spain, known for its mix of residential neighborhoods, cultural venues, and proximity to the Manzanares River.
  • B. Belén district
    Belén district is a riverside neighborhood in Iquitos, Peru, known for its stilt houses, floating structures, and bustling traditional market.
  • C. La Molina district
    La Molina district is an affluent residential and educational district located in the eastern part of Lima, Peru.
  • D. San Blas-Canillejas district
    The San Blas-Canillejas district is a largely residential area in the eastern part of Madrid, Spain, known for its mix of post-war neighborhoods, green spaces, and major transport links.
  • E. Al Olaya district
    Al Olaya district is a prominent commercial and business area in central Riyadh, Saudi Arabia, known for its modern skyscrapers, shopping centers, and major landmarks.
  • 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_69c008cd17c8819082b82d3fbeb68047 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063fc906481908283c6c50a212515 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5196defc08190810c6d208ade918b completed March 26, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:26 p.m.