Triple

T14902562
Position Surface form Disambiguated ID Type / Status
Subject Hendrika E360042 entity
Predicate relatedName P3889 FINISHED
Object Henrika
Henrika is a feminine given name, often considered a variant of Hendrika used in various European countries.
 E360042 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: Henrika | Statement: [Hendrika, relatedName, Henrika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henrika
Context triple: [Hendrika, relatedName, Henrika]
  • A. Henrike
    Henrike is a feminine given name of German origin, serving as the female form of Heinrich.
  • B. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • C. Hendrika
    Hendrika is a feminine given name of Dutch origin, commonly used in the Netherlands and related to the name Hendrickje.
  • D. Maddalene
    Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
  • 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: Henrika
Triple: [Hendrika, relatedName, Henrika]
Generated description
Henrika is a feminine given name, often considered a variant of Hendrika used in various European countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Henrika
Target entity description: Henrika is a feminine given name, often considered a variant of Hendrika used in various European countries.
  • A. Henrike
    Henrike is a feminine given name of German origin, serving as the female form of Heinrich.
  • B. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • C. Hendrika chosen
    Hendrika is a feminine given name of Dutch origin, commonly used in the Netherlands and related to the name Hendrickje.
  • D. Maddalene
    Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
  • 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.

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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded60b24008190bd272c0d61329400 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72b4e4f88190af7e859d93dbbd28 completed May 8, 2026, 11:33 p.m.
NEDg Description generation batch_69fe7360c11481908e2e5127b466e31b completed May 8, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_69fe743c37308190a045ef5f0ade8508 completed May 8, 2026, 11:39 p.m.
Created at: April 10, 2026, 2:11 a.m.