Triple

T14604477
Position Surface form Disambiguated ID Type / Status
Subject Margarita Province E342791 entity
Predicate administrativeCenter P1474 FINISHED
Object La Asunción E1104693 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: La Asunción | Statement: [Margarita Province, administrativeCenter, La Asunción]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Asunción
Context triple: [Margarita Province, administrativeCenter, La Asunción]
  • A. La Asunción chosen
    La Asunción is a historic colonial-era city on Venezuela’s Margarita Island, known for its religious landmarks and role as an administrative and cultural center.
  • B. Asuncion
    Asuncion is a remote volcanic island in the Northern Mariana Islands, known for its steep stratovolcano and relatively undisturbed natural environment.
  • 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. Asunción
    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.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44bf67c8190b4c48a7715f9443e completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda91d05e48190ac945e381d6d5dd9 completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:25 a.m.