Triple

T10660449
Position Surface form Disambiguated ID Type / Status
Subject James Callis E251208 entity
Predicate familyName P18 FINISHED
Object Callis
Callis is an English-language surname borne by various notable individuals across fields such as acting, sports, and academia.
 E877462 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: Callis | Statement: [James Callis, familyName, Callis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Callis
Context triple: [James Callis, familyName, Callis]
  • A. Kalliste
    Kalliste is an ancient name, meaning "the most beautiful," historically used for the Aegean island of Thera (modern Santorini).
  • B. Keally
    Keally is a surname most notably associated with Francis Keally, an American architect active in the early to mid-20th century.
  • C. Clelles
    Clelles is a small commune in southeastern France’s Isère department, known as a gateway village to the Vercors Massif and the iconic Mont Aiguille.
  • D. Callide
    Callide is a rural state electoral district in Queensland, Australia, known for its agricultural and mining communities.
  • E. Joseph Calleia
    Joseph Calleia was a Maltese-American character actor known for his distinctive voice and frequent roles as villains or tough figures in Hollywood films of the 1930s and 1940s.
  • 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: Callis
Triple: [James Callis, familyName, Callis]
Generated description
Callis is an English-language surname borne by various notable individuals across fields such as acting, sports, and academia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Callis
Target entity description: Callis is an English-language surname borne by various notable individuals across fields such as acting, sports, and academia.
  • A. Kalliste
    Kalliste is an ancient name, meaning "the most beautiful," historically used for the Aegean island of Thera (modern Santorini).
  • B. Keally
    Keally is a surname most notably associated with Francis Keally, an American architect active in the early to mid-20th century.
  • C. Clelles
    Clelles is a small commune in southeastern France’s Isère department, known as a gateway village to the Vercors Massif and the iconic Mont Aiguille.
  • D. Callide
    Callide is a rural state electoral district in Queensland, Australia, known for its agricultural and mining communities.
  • E. Joseph Calleia
    Joseph Calleia was a Maltese-American character actor known for his distinctive voice and frequent roles as villains or tough figures in Hollywood films of the 1930s and 1940s.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6e017f97c8190b22765a6f1e6719d completed April 8, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a8cabc88190b430cb08ed0fc515 completed April 10, 2026, 10:32 p.m.
NEDg Description generation batch_69d97cd3eab48190a191f0d8278ef761 completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e13913081908dd1fb60fa44db05 completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 9:07 p.m.