Triple

T1183337
Position Surface form Disambiguated ID Type / Status
Subject Aconcagua River E25189 entity
Predicate flowsNear P350 FINISHED
Object San Felipe E79916 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 Felipe | Statement: [Aconcagua River, flowsNear, San Felipe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Felipe
Context triple: [Aconcagua River, flowsNear, San Felipe]
  • A. San Felipe chosen
    San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
  • B. San Carlos
    San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
  • C. San Carlos
    San Carlos is a Chilean city known as an agricultural and commercial center in the Ñuble Region.
  • D. San Carlos
    San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
  • E. Tacuba
    Tacuba is a historic neighborhood in Mexico City known for its colonial-era architecture and role as a former pre-Hispanic town.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd35fb888190adf1e5d0615fa725 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f3443588190af6c06383e904e7d completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:45 p.m.