Triple

T3236996
Position Surface form Disambiguated ID Type / Status
Subject The Visit E67877 entity
Predicate character P662 FINISHED
Object 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.
 E340312 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: [The Visit, character, Tyler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tyler
Context triple: [The Visit, character, Tyler]
  • A. Tyler
    Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
  • 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. Neal
    Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
  • D. Jay
    Jay is the surname of John Jay, a prominent American Founding Father and the first Chief Justice of the United States.
  • E. Jay
    Jay is a small town located in Santa Rosa County in the northwestern part of Florida.
  • 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: [The Visit, character, Tyler]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tyler
Target entity description: 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.
  • A. Tyler
    Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
  • 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. Neal
    Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
  • D. Jay
    Jay is the surname of John Jay, a prominent American Founding Father and the first Chief Justice of the United States.
  • E. Jay
    Jay is a small town located in Santa Rosa County in the northwestern part of Florida.
  • 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.