Triple

T16568079
Position Surface form Disambiguated ID Type / Status
Subject Frederica of Hanover E402514 entity
Predicate givenName P17 FINISHED
Object Frederica E845985 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: Frederica | Statement: [Frederica of Hanover, givenName, Frederica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frederica
Context triple: [Frederica of Hanover, givenName, Frederica]
  • A. Frederica chosen
    Frederica is a feminine given name of Germanic origin that has been borne by various European royals and notable women.
  • B. Anna Maria, Florida
    Anna Maria, Florida is a small, laid-back island city on Florida’s Gulf Coast known for its beaches, fishing piers, and Old Florida charm.
  • C. Kinlan
    Kinlan is a surname of Irish origin borne by individuals such as actor Laurence Kinlan.
  • D. Clearwater
    Clearwater is a coastal city in Florida known for its white-sand beaches, tourism, and location on the Gulf of Mexico within the greater Tampa Bay metropolitan area.
  • E. Clearwater
    Clearwater is a small town in British Columbia, Canada, known as a gateway to Wells Gray Provincial Park and its numerous waterfalls and outdoor recreation opportunities.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35772f6608190a125c7d3c199c3e2 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee3dcbc819087ea66b262585232 completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.