Triple

T24820524
Position Surface form Disambiguated ID Type / Status
Subject Golden Triangle of Mexican drug trafficking E621048 entity
Predicate roleInDrugTrade P46944 FINISHED
Object major source of marijuana for U.S. market LITERAL 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: major source of marijuana for U.S. market | Statement: [Golden Triangle of Mexican drug trafficking, roleInDrugTrade, major source of marijuana for U.S. market]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: roleInDrugTrade
Context triple: [Golden Triangle of Mexican drug trafficking, roleInDrugTrade, major source of marijuana for U.S. market]
  • A. typeOfDrugsTrafficked
    Indicates that one entity specifies the category or kind of drugs that are being trafficked in the context of a drug-trafficking activity.
  • B. roleInCrime chosen
    Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
  • C. roleInGangRelated
    Indicates that an entity holds a specific role or function within a gang-related context or activity.
  • D. roleInGang
    Indicates that an entity holds a specific position or function within a gang organization.
  • E. hasDrugAddictedProtagonist
    Indicates that the work’s main character is portrayed as being addicted to drugs.
  • F. None of above.

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_69e2fabfd4648190bd0e5c7f4dbb6cab completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f5ffc74fa481909b4fe24a9337f9eb completed May 2, 2026, 1:44 p.m.
PD Predicate disambiguation batch_69f5f7f99dc08190afcfb3bc4dfbec1d completed May 2, 2026, 1:11 p.m.
Created at: April 18, 2026, 5:04 a.m.