Triple

T17480568
Position Surface form Disambiguated ID Type / Status
Subject Costa Rican Route 34 E425646 entity
Predicate passesNear P416 FINISHED
Object Jacó 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: Jacó | Statement: [Costa Rican Route 34, passesNear, Jacó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jacó
Context triple: [Costa Rican Route 34, passesNear, Jacó]
  • A. Jacó chosen
    Jacó is a popular beach town on Costa Rica’s Pacific coast known for its surfing, nightlife, and tourism.
  • B. San Juan
    San Juan is a neighborhood within the municipality of Telde on the island of Gran Canaria in Spain’s Canary Islands.
  • C. San Juan
    San Juan is the capital and largest city of Argentina’s San Juan Province, known for its wine production, seismic activity, and Andean setting.
  • D. San Juan
    San Juan is the largest city and main cultural, economic, and tourism hub of Puerto Rico, known for its historic colonial architecture and vibrant coastal setting.
  • E. San Juan
    San Juan is a suburban town in Trinidad and Tobago located just east of the capital, Port of Spain, known for its bustling commercial activity and residential communities.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451bf1e8081909f4d4b8992412e62 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:48 a.m.