Triple

T14699044
Position Surface form Disambiguated ID Type / Status
Subject Caroline Catz E345241 entity
Predicate givenName P17 FINISHED
Object Caroline E239135 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 Catz, givenName, Caroline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caroline
Context triple: [Caroline Catz, givenName, Caroline]
  • A. Caroline
    Caroline was a British princess of the early 18th century, the daughter of King George II and Queen Caroline of Ansbach.
  • B. Caroline chosen
    Caroline is a feminine given name of French and Latin origin, commonly used in English-speaking and European countries.
  • C. Caroline
    Caroline is a rural town in Tompkins County, New York, known for its small communities, scenic landscapes, and proximity to the city of Ithaca.
  • D. Caroline
    "Caroline" is a breakout hip-hop single by American rapper Aminé, known for its catchy hook and playful storytelling.
  • E. Caroline
    Caroline is a Danish princess, known formally as Princess Wilhelmina Caroline of Denmark, who lived in the 18th century.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb604f88081908a677175045496d0 completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0841da48190991d5045954a32ab completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:28 a.m.