Triple

T893237
Position Surface form Disambiguated ID Type / Status
Subject Caroline Kennedy E19286 entity
Predicate givenName P17 FINISHED
Object Caroline E108099 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: Caroline | Statement: [Caroline Kennedy, givenName, Caroline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caroline
Context triple: [Caroline Kennedy, givenName, Caroline]
  • A. Caroline chosen
    Caroline is a rural town in Tompkins County, New York, known for its small communities, scenic landscapes, and proximity to the city of Ithaca.
  • B. Caroline
    Caroline von Humboldt was a German salonnière, art patron, and intellectual known for her influential role in Berlin’s cultural and scholarly life in the early 19th century.
  • C. Carine
    Carine is a feminine given name, often considered a variant of names like Catherine or Karine, used in various European languages.
  • D. Claire
    Claire is a feminine given name of French origin meaning "clear" or "bright," commonly used in English-speaking countries.
  • E. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad212cd8819091eb1b7d606f5afd completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee02a21c819088e6a137ea306efd completed March 4, 2026, 8:32 a.m.
Created at: March 1, 2026, 7:39 p.m.