Triple

T12644316
Position Surface form Disambiguated ID Type / Status
Subject Avenida Madero E301981 entity
Predicate formerName P65 FINISHED
Object Plateros E625497 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: Plateros | Statement: [Avenida Madero, formerName, Plateros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plateros
Context triple: [Avenida Madero, formerName, Plateros]
  • A. Plateros chosen
    Plateros is a major Catholic pilgrimage site in Zacatecas, Mexico, renowned for its sanctuary dedicated to the Santo Niño de Atocha.
  • B. Marchigüe
    Marchigüe is a rural commune and town in central Chile’s O’Higgins Region, known for its agricultural activities and traditional countryside character.
  • C. Rentería
    Rentería (Errenteria) is a town in the Basque province of Gipuzkoa in northern Spain, known for its industrial history and proximity to San Sebastián.
  • D. Panza
    Panza is the surname of Sancho Panza, the loyal squire and comic foil to Don Quixote in Miguel de Cervantes' classic novel.
  • E. Panza
    Panza is a locality within the municipality of Forio on the Italian island of Ischia, known as a small coastal village and tourist area.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9614bf2f881909976becdf747f4fb completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6687961d88190a605f17425ad7547 completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:17 p.m.