Triple

T1528844
Position Surface form Disambiguated ID Type / Status
Subject Helena Christensen E32395 entity
Predicate familyName P18 FINISHED
Object Christensen
Christensen is a common Danish surname borne by numerous notable individuals across fields such as fashion, sports, politics, and the arts.
 E173455 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: Christensen | Statement: [Helena Christensen, familyName, Christensen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Christensen
Context triple: [Helena Christensen, familyName, Christensen]
  • A. Robertsen
    Robertsen is a surname of likely Scandinavian origin, functioning as a patronymic variant of the name Roberts.
  • B. Tomlinson
    Tomlinson is a surname most notably associated with Ray Tomlinson, the American computer programmer credited with inventing networked email and introducing the "@" symbol in email addresses.
  • C. Nilsen
    Nilsen is a surname, primarily of Scandinavian origin, that serves as a variant spelling of Nelson.
  • D. Sloan
    Sloan is a small unincorporated community in Clark County, Nevada, located just south of Las Vegas along Interstate 15.
  • E. Sloan
    Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
  • 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: Christensen
Triple: [Helena Christensen, familyName, Christensen]
Generated description
Christensen is a common Danish surname borne by numerous notable individuals across fields such as fashion, sports, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Christensen
Target entity description: Christensen is a common Danish surname borne by numerous notable individuals across fields such as fashion, sports, politics, and the arts.
  • A. Robertsen
    Robertsen is a surname of likely Scandinavian origin, functioning as a patronymic variant of the name Roberts.
  • B. Tomlinson
    Tomlinson is a surname most notably associated with Ray Tomlinson, the American computer programmer credited with inventing networked email and introducing the "@" symbol in email addresses.
  • C. Nilsen
    Nilsen is a surname, primarily of Scandinavian origin, that serves as a variant spelling of Nelson.
  • D. Sloan
    Sloan is a small unincorporated community in Clark County, Nevada, located just south of Las Vegas along Interstate 15.
  • E. Sloan
    Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb1dfd1a48190804ca5f0fb6f5985 completed March 7, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad2955dc788190988ebf911714437b completed March 8, 2026, 7:46 a.m.
NEDg Description generation batch_69ad2a18a79c81908f04ba9aa55d52a0 completed March 8, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69ad2a8deae8819095731fdd1b4bd310 completed March 8, 2026, 7:51 a.m.
Created at: March 4, 2026, 7:26 p.m.