Triple

T11208640
Position Surface form Disambiguated ID Type / Status
Subject Puerto Rico Highway 22 E265243 entity
Predicate connects P390 FINISHED
Object Vega Baja E266990 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: Vega Baja | Statement: [Puerto Rico Highway 22, connects, Vega Baja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vega Baja
Context triple: [Puerto Rico Highway 22, connects, Vega Baja]
  • A. Vega Baja chosen
    Vega Baja is a coastal municipality in northern Puerto Rico known for its beaches, particularly Playa Puerto Nuevo, and its mix of urban and rural communities.
  • B. Tecate
    Tecate is a Mexican border city in the state of Baja California, known for its brewery and as a quieter alternative crossing point near Tijuana.
  • C. Villacarrillo
    Villacarrillo is a town and municipality in the province of Jaén in Andalusia, southern Spain, known for its surrounding olive groves and agricultural economy.
  • D. Baja
    Baja is a town in southern Hungary known for its location on the Danube River and its cultural and economic role in the Bačka region.
  • E. San Ysidro
    San Ysidro is a community in the southernmost part of San Diego, California, best known for hosting one of the world’s busiest land border crossings between the United States and Mexico.
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8d5f8908190903817f84c629ba1 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad135154819091026334d25cd287 completed April 19, 2026, 10:23 a.m.
Created at: April 8, 2026, 9:30 p.m.