Triple

T519745
Position Surface form Disambiguated ID Type / Status
Subject Baja California E10786 entity
Predicate contains P35 FINISHED
Object Tecate E14747 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: Tecate | Statement: [Baja California, contains, Tecate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tecate
Context triple: [Baja California, contains, Tecate]
  • A. Tecate chosen
    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.
  • B. Tecate, California
    Tecate, California is a small border town in eastern San Diego County known for its international crossing with Tecate, Mexico and its role as a gateway between the two countries.
  • C. Tacuba
    Tacuba is a historic neighborhood in Mexico City known for its colonial-era architecture and role as a former pre-Hispanic town.
  • D. Ensenada
    Ensenada is a coastal city in northwestern Baja California, Mexico, known for its busy port, tourism, and nearby wine-producing valleys.
  • E. Rosarito
    Rosarito is a coastal resort city in northern Baja California, Mexico, known for its beaches, tourism, and proximity to the U.S. border.
  • 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_69a5089817248190b53d78e5b937026b completed March 2, 2026, 3:48 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.