Triple

T13983177
Position Surface form Disambiguated ID Type / Status
Subject Return to Sender E336365 entity
Predicate protagonist P268 FINISHED
Object Tyler
Tyler is the main character of the film "Return to Sender," around whom the story’s central events and conflicts revolve.
 E1074139 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: Tyler | Statement: [Return to Sender, protagonist, Tyler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tyler
Context triple: [Return to Sender, protagonist, Tyler]
  • A. Tyler
    Tyler is a character in the 2015 horror-thriller film "The Visit," serving as one of the two grandchildren whose unsettling stay with their grandparents drives the movie’s plot.
  • B. Tyler
    Tyler is a surname most prominently associated with American actress Liv Tyler and various other notable figures in entertainment and public life.
  • C. Tyler
    Tyler is a mid-sized city in East Texas known for its rose cultivation, annual Texas Rose Festival, and role as a regional medical and educational hub.
  • D. Tyler
    Tyler is a fictional character appearing in the American television series "Kristin."
  • E. Tyler
    Tyler is a masculine given name commonly used in English-speaking countries, originally derived from an occupational surname meaning "tile maker" or "house builder."
  • 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: Tyler
Triple: [Return to Sender, protagonist, Tyler]
Generated description
Tyler is the main character of the film "Return to Sender," around whom the story’s central events and conflicts revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tyler
Target entity description: Tyler is the main character of the film "Return to Sender," around whom the story’s central events and conflicts revolve.
  • A. Tyler
    Tyler is a character in the 2015 horror-thriller film "The Visit," serving as one of the two grandchildren whose unsettling stay with their grandparents drives the movie’s plot.
  • B. Tyler
    Tyler is a fictional character appearing in the American television series "Kristin."
  • C. Tyler
    Tyler is a surname most prominently associated with American actress Liv Tyler and various other notable figures in entertainment and public life.
  • D. Tyler
    Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
  • E. Tyler
    Tyler is a masculine given name commonly used in English-speaking countries, originally derived from an occupational surname meaning "tile maker" or "house builder."
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea2e8808190a1203a6386224bd8 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9231888190ad8cb460db73bdb4 completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbaf8dc2088190bd69f760ff15c03d completed May 6, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_69fbb01071408190a85e5e9be0150593 completed May 6, 2026, 9:18 p.m.
Created at: April 9, 2026, 10:18 p.m.