Triple

T373357
Position Surface form Disambiguated ID Type / Status
Subject Monterrey E8316 entity
Predicate officialName P66 FINISHED
Object Monterrey E8316 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: Monterrey | Statement: [Monterrey, officialName, Monterrey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monterrey
Context triple: [Monterrey, officialName, Monterrey]
  • A. Monterrey chosen
    Monterrey is a major industrial and economic hub in northeastern Mexico, known for its modern skyline, strong manufacturing base, and role as a center of business and education.
  • B. Guadalajara
    Guadalajara is a large cultural and economic hub in western Mexico, renowned for its colonial architecture, mariachi music, and role as a major center of industry and technology.
  • C. Mexico City
    Mexico City is the densely populated cultural, political, and economic center of Mexico, known for its rich history, colonial architecture, and vibrant urban life.
  • D. Tijuana
    Tijuana is a large, bustling border city in northwestern Mexico known for its cultural vibrancy, manufacturing industry, and close economic and social ties with the neighboring U.S. city of San Diego.
  • E. San Luis Potosí
    San Luis Potosí is a central Mexican state known for its diverse landscapes—from the arid high plateau to the lush Huasteca region—rich mining history, and colonial-era architecture.
  • 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_69a2e7f2ec648190b42bc7db424f8109 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec018d508190b5687a9ba90b3092 completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4429d10d88190ac5407bf4e539d4f completed March 1, 2026, 1:43 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.