Triple

T3998153
Position Surface form Disambiguated ID Type / Status
Subject Paul Anka E87147 entity
Predicate mother P120 FINISHED
Object Camelia Tannis
Camelia Tannis is the mother of Canadian-American singer, songwriter, and actor Paul Anka.
E407361 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: Camelia Tannis | Statement: [Paul Anka, mother, Camelia Tannis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camelia Tannis
Context triple: [Paul Anka, mother, Camelia Tannis]
  • A. Alexina Fall
    Alexina Fall was a member of the Fall family, known primarily as the daughter of Albert B. Fall, the U.S. Secretary of the Interior implicated in the Teapot Dome scandal.
  • B. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • C. Bayta Darell
    Bayta Darell is a pivotal character in Isaac Asimov's Foundation series, known for her crucial role in thwarting the Mule's conquest in "Foundation and Empire."
  • D. Tania
    Tania is a feminine given name commonly used as a diminutive or variant of names like Tatyana or Tatiana.
  • E. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-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: Camelia Tannis
Triple: [Paul Anka, mother, Camelia Tannis]
Generated description
Camelia Tannis is the mother of Canadian-American singer, songwriter, and actor Paul Anka.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Camelia Tannis
Target entity description: Camelia Tannis is the mother of Canadian-American singer, songwriter, and actor Paul Anka.
  • A. Alexina Fall
    Alexina Fall was a member of the Fall family, known primarily as the daughter of Albert B. Fall, the U.S. Secretary of the Interior implicated in the Teapot Dome scandal.
  • B. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • C. Bayta Darell
    Bayta Darell is a pivotal character in Isaac Asimov's Foundation series, known for her crucial role in thwarting the Mule's conquest in "Foundation and Empire."
  • D. Tania
    Tania is a feminine given name commonly used as a diminutive or variant of names like Tatyana or Tatiana.
  • E. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa3ef7ac8190abe02f440ff83c43 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c54f05c8190b18c2d4839a61b64 completed March 14, 2026, 11:53 a.m.
NEDg Description generation batch_69b54cf3da208190aa844c9ea66354fe completed March 14, 2026, 11:56 a.m.
NED2 Entity disambiguation (via description) batch_69b55159dc288190a63d5f5164b73bbb completed March 14, 2026, 12:15 p.m.
Created at: March 9, 2026, 3:34 p.m.