Triple

T3236995
Position Surface form Disambiguated ID Type / Status
Subject The Visit E67877 entity
Predicate character P662 FINISHED
Object Becca
Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
 E340311 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: Becca | Statement: [The Visit, character, Becca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Becca
Context triple: [The Visit, character, Becca]
  • A. Becky
    Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
  • B. Rebeca
    Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
  • C. Bella Higginbotham
    Bella Higginbotham is an American actress best known for her role in the film "Troop Zero" and for appearing in various television and streaming series.
  • D. Hadley Beeman
    Hadley Beeman is a web standards and technology governance expert known for her leadership within the World Wide Web Consortium (W3C) and related digital policy initiatives.
  • E. Jenna
    Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
  • 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: Becca
Triple: [The Visit, character, Becca]
Generated description
Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Becca
Target entity description: Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
  • A. Becky
    Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
  • B. Rebeca
    Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
  • C. Bella Higginbotham
    Bella Higginbotham is an American actress best known for her role in the film "Troop Zero" and for appearing in various television and streaming series.
  • D. Hadley Beeman
    Hadley Beeman is a web standards and technology governance expert known for her leadership within the World Wide Web Consortium (W3C) and related digital policy initiatives.
  • E. Jenna
    Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef29bf48190a9aa3a39f0138428 completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b277459d1081909766934ce6a56091 completed March 12, 2026, 8:20 a.m.
NEDg Description generation batch_69b2780e41e0819080ddb26668f32838 completed March 12, 2026, 8:23 a.m.
NED2 Entity disambiguation (via description) batch_69b27bd238a48190b9d13ee8a8bc955d completed March 12, 2026, 8:39 a.m.
Created at: March 8, 2026, 3:08 p.m.