Triple

T7157692
Position Surface form Disambiguated ID Type / Status
Subject President of Venezuela E166856 entity
Predicate seat P75 FINISHED
Object Caracas E54898 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: Caracas | Statement: [President of Venezuela, seat, Caracas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caracas
Context triple: [President of Venezuela, seat, Caracas]
  • A. Caracas chosen
    Caracas is the capital and largest city of Venezuela, known as a major political, cultural, and economic center in northern South America.
  • B. Maracaibo
    Maracaibo is a major Venezuelan city known as an important oil-producing and commercial center located on the western shore of Lake Maracaibo.
  • C. Barquisimeto
    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.
  • D. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • E. Santa Marta
    Santa Marta is a historic Caribbean port city in northern Colombia and one of the oldest surviving Spanish settlements in 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_69c68887a5cc8190bec0ea96227164f7 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e80f14808190907ee84523630d85 completed March 27, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8fae30481909c39d68fb828a2c0 completed March 28, 2026, 11:18 a.m.
Created at: March 27, 2026, 2:47 p.m.