Triple

T17777862
Position Surface form Disambiguated ID Type / Status
Subject Revolución E443818 entity
Predicate adjacentStationOnLine2 P81819 FINISHED
Object San Cosme NE NERFINISHED

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 Cosme | Statement: [Revolución, adjacentStationOnLine2, San Cosme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Cosme
Context triple: [Revolución, adjacentStationOnLine2, San Cosme]
  • A. San Cosme chosen
    San Cosme is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near the historic center of the city.
  • B. San Pascual
    San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
  • C. San Pascual
    San Pascual is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
  • D. San Pascual
    San Pascual is a coastal municipality in the Philippine province of Masbate known for its island landscapes and fishing-based local economy.
  • E. San Juan de Flores
    San Juan de Flores is a municipality in central Honduras known for its rural character and location within the Francisco Morazán Department.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871e06a481909cf6d59e49dc21c5 completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:12 a.m.