Triple

T1225791
Position Surface form Disambiguated ID Type / Status
Subject Glitter E26323 entity
Predicate starring P1507 FINISHED
Object Tia Texada
Tia Texada is an American actress and voice artist known for her roles in film and television, including a notable appearance in the early-2000s music drama "Glitter."
E140719 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: Tia Texada | Statement: [Glitter, starring, Tia Texada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tia Texada
Context triple: [Glitter, starring, Tia Texada]
  • A. Alexa Vega
    Alexa Vega is an American actress and singer best known for playing Carmen Cortez in the Spy Kids film series.
  • B. Carmen Cortez
    Carmen Cortez is a resourceful young spy and one of the two sibling protagonists in the Spy Kids film series.
  • C. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • D. Amada Cruz
    Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
  • E. Tita de la Garza
    Tita de la Garza is the passionate, emotionally expressive heroine of Laura Esquivel’s novel "Like Water for Chocolate," whose cooking magically channels her feelings.
  • 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: Tia Texada
Triple: [Glitter, starring, Tia Texada]
Generated description
Tia Texada is an American actress and voice artist known for her roles in film and television, including a notable appearance in the early-2000s music drama "Glitter."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tia Texada
Target entity description: Tia Texada is an American actress and voice artist known for her roles in film and television, including a notable appearance in the early-2000s music drama "Glitter."
  • A. Alexa Vega
    Alexa Vega is an American actress and singer best known for playing Carmen Cortez in the Spy Kids film series.
  • B. Carmen Cortez
    Carmen Cortez is a resourceful young spy and one of the two sibling protagonists in the Spy Kids film series.
  • C. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • D. Amada Cruz
    Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
  • E. Tita de la Garza
    Tita de la Garza is the passionate, emotionally expressive heroine of Laura Esquivel’s novel "Like Water for Chocolate," whose cooking magically channels her feelings.
  • 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_69a49484688c8190a1bf285eb396a8b6 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be39908481908cca21aaf0828415 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a0fcf508190be3668bd55f6f6d6 completed March 7, 2026, 8:26 p.m.
NEDg Description generation batch_69ac8ab214c48190a60c6604a67f9cf2 completed March 7, 2026, 8:29 p.m.
NED2 Entity disambiguation (via description) batch_69ac8b0db83c81909db3c501a435f1d1 completed March 7, 2026, 8:31 p.m.
Created at: March 1, 2026, 7:47 p.m.