Triple

T6232340
Position Surface form Disambiguated ID Type / Status
Subject Vista E139385 entity
Predicate adjacentTo P224 FINISHED
Object San Marcos E139386 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: San Marcos | Statement: [Vista, adjacentTo, San Marcos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Marcos
Context triple: [Vista, adjacentTo, San Marcos]
  • A. San Marcos
    San Marcos is a city in western Guatemala that serves as the capital of the San Marcos Department near the country’s highest peak, Volcán Tajumulco.
  • B. San Marcos
    San Marcos is a city that maintains an official twinning partnership with Biel/Bienne in Switzerland, reflecting cultural and municipal cooperation between the two communities.
  • C. San Marcos chosen
    San Marcos is a suburban city in northern San Diego County, California, known for its growing residential communities and educational institutions such as California State University San Marcos.
  • D. San Marcos
    San Marcos is a municipality located in the Sucre Department of northern Colombia, known for its role in the region’s agricultural and cattle-raising economy.
  • E. San Marcos, Texas
    San Marcos, Texas is a central Texas city along the San Marcos River known for its university campus, outlet shopping, and outdoor recreation.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062ee6f088190bf72692eb8ffb761 completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c243f785dc819084d2a11151d84227 completed March 24, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:22 p.m.