Triple

T3553349
Position Surface form Disambiguated ID Type / Status
Subject Guaviare River E75160 entity
Predicate flowsThrough P225 FINISHED
Object Meta Department E31474 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: Meta Department | Statement: [Guaviare River, flowsThrough, Meta Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meta Department
Context triple: [Guaviare River, flowsThrough, Meta Department]
  • A. Meta Department chosen
    Meta Department is an administrative region in central Colombia known for its vast plains (Llanos), agriculture, and oil production.
  • B. Home Department
    The Home Department was a former British government ministry responsible for domestic affairs, which was later reorganized and succeeded by the Home Office.
  • C. Var department
    Var department is an administrative division in the Provence-Alpes-Côte d'Azur region of southeastern France, known for its Mediterranean coastline, resorts, and historic towns.
  • D. Dictionary Department
    The Dictionary Department is the division of the Royal Spanish Academy responsible for researching, updating, and producing its official dictionaries of the Spanish language.
  • E. Department of Marketing
    The Department of Marketing is an academic unit at the Vienna University of Economics and Business specializing in research and education on marketing strategy, consumer behavior, and market analysis.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc05394888190b59fafda97b49beb completed March 8, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb9218448190ae432ae74c0a6916 completed March 13, 2026, 7:24 a.m.
Created at: March 8, 2026, 3:20 p.m.