Triple

T519744
Position Surface form Disambiguated ID Type / Status
Subject Baja California E10786 entity
Predicate contains P35 FINISHED
Object Ensenada E52353 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: Ensenada | Statement: [Baja California, contains, Ensenada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ensenada
Context triple: [Baja California, contains, Ensenada]
  • A. Ensenada chosen
    Ensenada is a coastal city in northwestern Baja California, Mexico, known for its busy port, tourism, and nearby wine-producing valleys.
  • B. Tijuana
    Tijuana is a large, bustling border city in northwestern Mexico known for its cultural vibrancy, manufacturing industry, and close economic and social ties with the neighboring U.S. city of San Diego.
  • C. Rosarito
    Rosarito is a coastal resort city in northern Baja California, Mexico, known for its beaches, tourism, and proximity to the U.S. border.
  • D. Colonia Juárez
    Colonia Juárez is a historic and centrally located neighborhood in Mexico City known for its eclectic architecture, cultural venues, and vibrant commercial and nightlife scenes.
  • E. Buenavista
    Buenavista is a major transit hub and neighborhood in Mexico City that serves as a key interchange point for metro, bus rapid transit, and commuter rail services.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1a00a6c8190a62dc7c901c2f2ff completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55a7165988190bc4312ca40770e27 completed March 2, 2026, 9:37 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.