Triple

T9837343
Position Surface form Disambiguated ID Type / Status
Subject Caroline E239135 entity
Predicate hasVariantSpelling P457 FINISHED
Object Karoline
Karoline is a feminine given name, commonly used in various European countries, that is a variant spelling of Caroline.
 E824727 NE FINISHED

How this triple was built (4 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: Karoline | Statement: [Caroline, hasVariantSpelling, Karoline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Karoline
Context triple: [Caroline, hasVariantSpelling, Karoline]
  • A. Cecilie
    Cecilie is a feminine given name, commonly used in Scandinavian countries, that is a variant of the name Cecilia.
  • B. Maria Karoline
    Maria Karoline is a female given name of European origin, often used in German-speaking countries.
  • C. Dagmar
    Dagmar is a feminine given name of Germanic origin, historically associated with European nobility and still used in various countries today.
  • D. Reine
    Reine is a picturesque fishing village in Norway’s Lofoten archipelago, known for its dramatic mountain backdrop and traditional red rorbuer cabins by the sea.
  • E. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Karoline
Triple: [Caroline, hasVariantSpelling, Karoline]
Generated description
Karoline is a feminine given name, commonly used in various European countries, that is a variant spelling of Caroline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Karoline
Target entity description: Karoline is a feminine given name, commonly used in various European countries, that is a variant spelling of Caroline.
  • A. Cecilie
    Cecilie is a feminine given name, commonly used in Scandinavian countries, that is a variant of the name Cecilia.
  • B. Maria Karoline
    Maria Karoline is a female given name of European origin, often used in German-speaking countries.
  • C. Dagmar
    Dagmar is a feminine given name of Germanic origin, historically associated with European nobility and still used in various countries today.
  • D. Reine
    Reine is a picturesque fishing village in Norway’s Lofoten archipelago, known for its dramatic mountain backdrop and traditional red rorbuer cabins by the sea.
  • E. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • F. None of above. chosen

Provenance (5 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb347ff4c81908c312548a25bae71 completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5ccb28c8190a580767a57474557 completed April 5, 2026, 3:23 a.m.
NEDg Description generation batch_69d1d66e91c881909eae9d539f47bd99 completed April 5, 2026, 3:26 a.m.
NED2 Entity disambiguation (via description) batch_69d1d6dc0bd8819082a5ad417ca87a76 completed April 5, 2026, 3:28 a.m.
Created at: March 30, 2026, 8:33 p.m.