Triple

T3623644
Position Surface form Disambiguated ID Type / Status
Subject Alexa Vega E76784 entity
Predicate performedIn P795 FINISHED
Object Sleepover
Sleepover is a 2004 teen comedy film about a group of girls whose overnight party turns into a series of adventurous dares and misadventures.
 E373818 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: Sleepover | Statement: [Alexa Vega, performedIn, Sleepover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sleepover
Context triple: [Alexa Vega, performedIn, Sleepover]
  • A. The Babysitters
    The Babysitters is a poem by Sylvia Plath that reflects her characteristic blend of domestic imagery and psychological intensity.
  • B. A Night Out
    A Night Out is a 1915 silent comedy film starring Charlie Chaplin, produced during his early period in American cinema.
  • C. Bedtime
    "Bedtime" is a British television drama series best known for its intimate, character-driven stories set around the lives of neighbors in a suburban street at night.
  • D. Save the Night
    "Save the Night" is a song by John Legend from his R&B album "Love in the Future."
  • E. The Spare Room
    The Spare Room is a critically acclaimed novel by Australian writer Helen Garner that explores friendship, mortality, and the emotional toll of caring for a terminally ill loved one.
  • 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: Sleepover
Triple: [Alexa Vega, performedIn, Sleepover]
Generated description
Sleepover is a 2004 teen comedy film about a group of girls whose overnight party turns into a series of adventurous dares and misadventures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sleepover
Target entity description: Sleepover is a 2004 teen comedy film about a group of girls whose overnight party turns into a series of adventurous dares and misadventures.
  • A. The Babysitters
    The Babysitters is a poem by Sylvia Plath that reflects her characteristic blend of domestic imagery and psychological intensity.
  • B. A Night Out
    A Night Out is a 1915 silent comedy film starring Charlie Chaplin, produced during his early period in American cinema.
  • C. Bedtime
    "Bedtime" is a British television drama series best known for its intimate, character-driven stories set around the lives of neighbors in a suburban street at night.
  • D. Save the Night
    "Save the Night" is a song by John Legend from his R&B album "Love in the Future."
  • E. The Spare Room
    The Spare Room is a critically acclaimed novel by Australian writer Helen Garner that explores friendship, mortality, and the emotional toll of caring for a terminally ill loved one.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2bc79008190abe6900adcbda8de completed March 8, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b43320955c8190910c0f15c80f41f4 completed March 13, 2026, 3:54 p.m.
NEDg Description generation batch_69b43705642881909c62b7363a4f3a12 completed March 13, 2026, 4:10 p.m.
NED2 Entity disambiguation (via description) batch_69b4379cd04c81909246747bcc357261 completed March 13, 2026, 4:13 p.m.
Created at: March 8, 2026, 3:23 p.m.