Triple

T11992573
Position Surface form Disambiguated ID Type / Status
Subject Tye Sheridan E285444 entity
Predicate givenName P17 FINISHED
Object Tye
Tye is the first name of American actor Tye Sheridan, known for roles in films like "Mud," "Ready Player One," and the "X-Men" series.
 E958568 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: Tye | Statement: [Tye Sheridan, givenName, Tye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tye
Context triple: [Tye Sheridan, givenName, Tye]
  • A. Tyrel
    Tyrel is a 2018 American drama film that follows a young Black man who joins a group of white friends on a tense, alcohol-fueled weekend trip in the Catskills.
  • B. Tyrus Kitt
    Tyrus Kitt is a stoic and highly competent enforcer and security specialist who works as one of Gustavo Fring’s most trusted henchmen in the Breaking Bad universe.
  • C. Sawyer
    Sawyer is a surname of English origin commonly borne by individuals in English-speaking countries.
  • D. Sawyer
    Sawyer is a collaborative industrial robot arm developed by Rethink Robotics for flexible, safe automation tasks alongside human workers.
  • E. Maddox
    Maddox is the eldest son of actors Angelina Jolie and Brad Pitt, known for largely growing up in the public eye.
  • 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: Tye
Triple: [Tye Sheridan, givenName, Tye]
Generated description
Tye is the first name of American actor Tye Sheridan, known for roles in films like "Mud," "Ready Player One," and the "X-Men" series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tye
Target entity description: Tye is the first name of American actor Tye Sheridan, known for roles in films like "Mud," "Ready Player One," and the "X-Men" series.
  • A. Tyrel
    Tyrel is a 2018 American drama film that follows a young Black man who joins a group of white friends on a tense, alcohol-fueled weekend trip in the Catskills.
  • B. Tyrus Kitt
    Tyrus Kitt is a stoic and highly competent enforcer and security specialist who works as one of Gustavo Fring’s most trusted henchmen in the Breaking Bad universe.
  • C. Sawyer
    Sawyer is a surname of English origin commonly borne by individuals in English-speaking countries.
  • D. Sawyer
    Sawyer is a collaborative industrial robot arm developed by Rethink Robotics for flexible, safe automation tasks alongside human workers.
  • E. Maddox
    Maddox is the eldest son of actors Angelina Jolie and Brad Pitt, known for largely growing up in the public eye.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b11ac481909866b611380792e7 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4726696dc8190bf2a7aa43cb08b19 completed May 1, 2026, 9:29 a.m.
NEDg Description generation batch_69f47b7d4ef081908f7f87d90c00d9ed completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47de8c9e48190af01918c9cd94c7d completed May 1, 2026, 10:18 a.m.
Created at: April 8, 2026, 9:46 p.m.