Triple

T13161666
Position Surface form Disambiguated ID Type / Status
Subject Jefferson Parish E312740 entity
Predicate contains P35 FINISHED
Object Lafitte E1018232 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: Lafitte | Statement: [Jefferson Parish, contains, Lafitte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lafitte
Context triple: [Jefferson Parish, contains, Lafitte]
  • A. Lafitte chosen
    Lafitte is a French-origin surname borne by various notable individuals, including figures in politics, the arts, and sports.
  • B. San Nicolas
    San Nicolas is a town in Aruba known for its significant Afro-Aruban community and cultural influence.
  • C. San Nicolas
    San Nicolas is a historic riverside district of Manila, Philippines, known for its old commercial houses, narrow streets, and proximity to the walled city of Intramuros.
  • D. San Nicolas
    San Nicolas is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • E. San Nicolas
    San Nicolas is a municipality in the Philippine province of Ilocos Norte known for its historical heritage and role as a commercial and industrial hub in the region.
  • 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_69d806ac3ee081909b2fd27d060aa974 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c0a9d348190909fcf45f9d650e4 completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaf4cd788190b74cca51b5219bfb completed May 3, 2026, 6:28 a.m.
Created at: April 9, 2026, 9:12 p.m.