Triple

T13983179
Position Surface form Disambiguated ID Type / Status
Subject Return to Sender E336365 entity
Predicate character P662 FINISHED
Object Tyler
Tyler is a fictional character from the film "Return to Sender," involved in the psychological thriller’s central storyline.
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, character, Tyler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyler
Context triple: [Return to Sender, character, 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, character, Tyler]
Generated description
Tyler is a fictional character from the film "Return to Sender," involved in the psychological thriller’s central storyline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tyler
Target entity description: Tyler is a fictional character from the film "Return to Sender," involved in the psychological thriller’s central storyline.
  • A. Tyler chosen
    Tyler is the main character of the film "Return to Sender," around whom the story’s central events and conflicts revolve.
  • B. 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.
  • C. Tyler
    Tyler is a fictional character appearing in the American television series "Kristin."
  • D. Tyler
    Tyler is a surname most prominently associated with American actress Liv Tyler and various other notable figures in entertainment and public life.
  • E. Tyler
    Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
  • F. None of above.

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_69fbc32593e08190a1fe8466705c7fe8 completed May 6, 2026, 10:39 p.m.
NEDg Description generation batch_69fc4348617881908262390a447ad7af completed May 7, 2026, 7:46 a.m.
NED2 Entity disambiguation (via description) batch_69fc446397988190bb0e415680312ac0 completed May 7, 2026, 7:50 a.m.
Created at: April 9, 2026, 10:18 p.m.