Triple

T10917705
Position Surface form Disambiguated ID Type / Status
Subject Sweet Sixteen E257866 entity
Predicate stars P1956 FINISHED
Object Annmarie Fulton
Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
E1061095 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: Annmarie Fulton | Statement: [Sweet Sixteen, stars, Annmarie Fulton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annmarie Fulton
Context triple: [Sweet Sixteen, stars, Annmarie Fulton]
  • A. Laura Bickford
    Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
  • B. Annmarie Powell
    Annmarie Powell is one of the daughters of Alma Johnson Powell and former U.S. Secretary of State Colin Powell.
  • C. Colleen Farrington
    Colleen Farrington was an American model and nightclub singer best known as the mother of actress Diane Lane.
  • D. Laura Merriman
    Laura Merriman is known as the spouse of Dwight Merriman, the co-founder and former CEO of DoubleClick and co-founder of MongoDB.
  • E. Milynn Sarley
    Milynn Sarley is an American actress and internet personality known for her roles in low-budget fantasy and action films as well as her presence in online geek and gaming communities.
  • 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: Annmarie Fulton
Triple: [Sweet Sixteen, stars, Annmarie Fulton]
Generated description
Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Annmarie Fulton
Target entity description: Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
  • A. Laura Bickford
    Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
  • B. Annmarie Powell
    Annmarie Powell is one of the daughters of Alma Johnson Powell and former U.S. Secretary of State Colin Powell.
  • C. Colleen Farrington
    Colleen Farrington was an American model and nightclub singer best known as the mother of actress Diane Lane.
  • D. Laura Merriman
    Laura Merriman is known as the spouse of Dwight Merriman, the co-founder and former CEO of DoubleClick and co-founder of MongoDB.
  • E. Milynn Sarley
    Milynn Sarley is an American actress and internet personality known for her roles in low-budget fantasy and action films as well as her presence in online geek and gaming communities.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7707ebdcc8190b42cafe21c667c82 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b0513f408190b822566b8fc771cd completed May 3, 2026, 8:30 p.m.
NEDg Description generation batch_69f7b14fe1cc8190b1a5f6f0e80b7e39 completed May 3, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69f7b20f67048190a641527353e3ff43 completed May 3, 2026, 8:37 p.m.
Created at: April 8, 2026, 9:22 p.m.