Triple

T17773113
Position Surface form Disambiguated ID Type / Status
Subject Óscar Rodríguez E443690 entity
Predicate sphereOfInfluence P2828 FINISHED
Object Asunción NE NERFINISHED

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: Asunción | Statement: [Óscar Rodríguez, sphereOfInfluence, Asunción]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asunción
Context triple: [Óscar Rodríguez, sphereOfInfluence, Asunción]
  • A. Asunción chosen
    Asunción is the capital and largest city of Paraguay, located along the Paraguay River and serving as the country’s main political, cultural, and economic center.
  • B. Asunción
    Asunción is the birth name of American lawyer, journalist, and television host Sunny Hostin.
  • C. Asuncion
    Asuncion is a stage play written by actor and playwright Jesse Eisenberg that explores themes of privilege, prejudice, and cultural misunderstanding.
  • D. Asuncion
    Asuncion is a rural municipality in the province of Davao del Norte on the island of Mindanao in the Philippines.
  • E. Asuncion
    Asuncion is a remote volcanic island in the Northern Mariana Islands, known for its steep stratovolcano and relatively undisturbed natural environment.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871a2130819081743ae89dddc64b completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:12 a.m.