Triple

T16283775
Position Surface form Disambiguated ID Type / Status
Subject Crista Flanagan E395334 entity
Predicate givenName P17 FINISHED
Object Crista
Crista is an American actress and comedian best known for her work on the sketch comedy show MADtv.
 E1204457 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: Crista | Statement: [Crista Flanagan, givenName, Crista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Crista
Context triple: [Crista Flanagan, givenName, Crista]
  • A. Crenna
    Crenna is a surname most notably associated with American actor and director Richard Crenna, known for his roles in film and television from the mid-20th century onward.
  • B. Crisa
    Crisa was an ancient Greek town near Delphi that played a central role in the First Sacred War over control of the sanctuary and its access routes.
  • C. Sphettus
    Sphettus was an ancient deme (district) of Attica in classical Greece, associated with several notable Athenian figures.
  • D. Crucita
    Crucita is a coastal town in Ecuador renowned for its beaches and paragliding, making it a popular seaside destination in Manabí Province.
  • E. Cairon
    Cairon is a small commune in the Calvados department of the Normandy region in northwestern France.
  • 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: Crista
Triple: [Crista Flanagan, givenName, Crista]
Generated description
Crista is an American actress and comedian best known for her work on the sketch comedy show MADtv.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Crista
Target entity description: Crista is an American actress and comedian best known for her work on the sketch comedy show MADtv.
  • A. Crenna
    Crenna is a surname most notably associated with American actor and director Richard Crenna, known for his roles in film and television from the mid-20th century onward.
  • B. Crisa
    Crisa was an ancient Greek town near Delphi that played a central role in the First Sacred War over control of the sanctuary and its access routes.
  • C. Sphettus
    Sphettus was an ancient deme (district) of Attica in classical Greece, associated with several notable Athenian figures.
  • D. Crucita
    Crucita is a coastal town in Ecuador renowned for its beaches and paragliding, making it a popular seaside destination in Manabí Province.
  • E. Cairon
    Cairon is a small commune in the Calvados department of the Normandy region in northwestern France.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24912c5808190a0d9c9f491315068 completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c8f51c8190b73cdf2834eda57f completed May 10, 2026, 5:29 a.m.
NEDg Description generation batch_6a0019c847a0819081b92e21ced73824 completed May 10, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_6a001a7dcf888190b66122f2bfc7388b completed May 10, 2026, 5:41 a.m.
Created at: April 10, 2026, 5:05 a.m.