Triple

T10240067
Position Surface form Disambiguated ID Type / Status
Subject Lope de Aguirre E243563 entity
Predicate deathPlace P21 FINISHED
Object Barquisimeto E172131 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: Barquisimeto | Statement: [Lope de Aguirre, deathPlace, Barquisimeto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barquisimeto
Context triple: [Lope de Aguirre, deathPlace, Barquisimeto]
  • A. Barquisimeto chosen
    Barquisimeto is a major city in western Venezuela known as a commercial and cultural center, often called the "Musical City" for its rich musical traditions.
  • B. Maracay
    Maracay is a major industrial and commercial city in north-central Venezuela and the capital of Aragua state.
  • C. Maracaibo
    Maracaibo is a major Venezuelan city known as an important oil-producing and commercial center located on the western shore of Lake Maracaibo.
  • D. Puerto Cabello
    Puerto Cabello is a major port city on Venezuela’s Caribbean coast, historically important for trade and naval activity.
  • E. Caracas
    Caracas is the capital and largest city of Venezuela, known as a major political, cultural, and economic center in northern South America.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d21e27f08190b956d351a75c7c52 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f776464881908957e1ac4b49d936 completed April 9, 2026, 12:48 a.m.
Created at: April 6, 2026, 11:24 a.m.