Triple

T10267273
Position Surface form Disambiguated ID Type / Status
Subject Krystal E240739 entity
Predicate relatedName P3889 FINISHED
Object Kristel
Kristel is a given name commonly used for women in various countries, often considered a variant of Crystal/Krystal.
E853045 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: Kristel | Statement: [Krystal, relatedName, Kristel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristel
Context triple: [Krystal, relatedName, Kristel]
  • A. Cristolienne
    Cristolienne is the French term for a female inhabitant or native of the city of Créteil, located in the southeastern suburbs of Paris.
  • B. Christianne
    Christianne is a feminine given name of Latin origin, commonly used in German- and English-speaking countries.
  • C. Katarina Church
    Katarina Church is a historic Lutheran church in central Stockholm, Sweden, known for its Baroque architecture and prominent hilltop location on Södermalm.
  • D. Kristian
    Kristian is a given name notably borne by Lauri Kristian Relander, the second President of Finland.
  • E. Crist
    Crist is a surname most prominently associated with American politician Charlie Crist, a former governor of Florida.
  • 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: Kristel
Triple: [Krystal, relatedName, Kristel]
Generated description
Kristel is a given name commonly used for women in various countries, often considered a variant of Crystal/Krystal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kristel
Target entity description: Kristel is a given name commonly used for women in various countries, often considered a variant of Crystal/Krystal.
  • A. Cristolienne
    Cristolienne is the French term for a female inhabitant or native of the city of Créteil, located in the southeastern suburbs of Paris.
  • B. Christianne
    Christianne is a feminine given name of Latin origin, commonly used in German- and English-speaking countries.
  • C. Katarina Church
    Katarina Church is a historic Lutheran church in central Stockholm, Sweden, known for its Baroque architecture and prominent hilltop location on Södermalm.
  • D. Kristian
    Kristian is a given name notably borne by Lauri Kristian Relander, the second President of Finland.
  • E. Crist
    Crist is a surname most prominently associated with American politician Charlie Crist, a former governor of Florida.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d26df80081908514fd5c9392e2b7 completed April 7, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f805d49c8190becddbbf17ac65fd completed April 9, 2026, 12:51 a.m.
NEDg Description generation batch_69d6fcaca55c81908a48ac2a0ce24b85 completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd772bc08190bf270f5fc767fb29 completed April 9, 2026, 1:14 a.m.
Created at: April 6, 2026, 11:34 a.m.