Triple

T977006
Position Surface form Disambiguated ID Type / Status
Subject Little Women (1994 film) E21075 entity
Predicate stars P1956 FINISHED
Object Trini Alvarado
Trini Alvarado is an American actress known for her nuanced performances in films such as "Little Women" (1994) and "The Frighteners."
E132373 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: Trini Alvarado | Statement: [Little Women (1994 film), stars, Trini Alvarado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trini Alvarado
Context triple: [Little Women (1994 film), stars, Trini Alvarado]
  • A. Michelle Navarro
    Michelle Navarro is an individual notable enough to be recognized as a prominent bearer of the Navarro surname.
  • B. Daniela Andrade
    Daniela Andrade is a Canadian singer-songwriter and YouTube artist known for her intimate acoustic covers and original indie-pop music.
  • C. Elizabeth Avellán
    Elizabeth Avellán is a Venezuelan-American film producer known for co-founding Troublemaker Studios and producing many of Robert Rodriguez’s films.
  • D. Ivana Baquero
    Ivana Baquero is a Spanish actress best known for her acclaimed performance as the young protagonist in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
  • E. Silvia Navarro
    Silvia Navarro is a Mexican actress best known for her leading roles in popular telenovelas and television dramas.
  • 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: Trini Alvarado
Triple: [Little Women (1994 film), stars, Trini Alvarado]
Generated description
Trini Alvarado is an American actress known for her nuanced performances in films such as "Little Women" (1994) and "The Frighteners."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Trini Alvarado
Target entity description: Trini Alvarado is an American actress known for her nuanced performances in films such as "Little Women" (1994) and "The Frighteners."
  • A. Michelle Navarro
    Michelle Navarro is an individual notable enough to be recognized as a prominent bearer of the Navarro surname.
  • B. Daniela Andrade
    Daniela Andrade is a Canadian singer-songwriter and YouTube artist known for her intimate acoustic covers and original indie-pop music.
  • C. Elizabeth Avellán
    Elizabeth Avellán is a Venezuelan-American film producer known for co-founding Troublemaker Studios and producing many of Robert Rodriguez’s films.
  • D. Ivana Baquero
    Ivana Baquero is a Spanish actress best known for her acclaimed performance as the young protagonist in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
  • E. Silvia Navarro
    Silvia Navarro is a Mexican actress best known for her leading roles in popular telenovelas and television dramas.
  • 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_69a493c2b62c8190b616351789ec47f8 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b46344048190b7a13b8f3ad9f455 completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5e9b74e481908c7d8256bd180d73 completed March 7, 2026, 5:21 p.m.
NEDg Description generation batch_69ac5f9a8a648190b2e677db032be07c completed March 7, 2026, 5:25 p.m.
NED2 Entity disambiguation (via description) batch_69ac5feabffc819082f5d28f9628558f completed March 7, 2026, 5:27 p.m.
Created at: March 1, 2026, 7:40 p.m.