Triple

T10527475
Position Surface form Disambiguated ID Type / Status
Subject Lopez vs Lopez E248343 entity
Predicate starring P1507 FINISHED
Object Matt Shively
Matt Shively is an American actor best known for his comedic roles on television, including his co-starring role in the sitcom "Lopez vs Lopez."
E892002 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: Matt Shively | Statement: [Lopez vs Lopez, starring, Matt Shively]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Shively
Context triple: [Lopez vs Lopez, starring, Matt Shively]
  • A. Matt Sherring
    Matt Sherring is a screenwriter best known for writing the action thriller film "Killer Elite."
  • B. Matthew Shoemaker
    Matthew Shoemaker is a Canadian municipal politician serving as the mayor of Sault Ste. Marie, Ontario.
  • C. Brant Daugherty
    Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
  • D. Matt Graver
    Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
  • E. Josh Schaeffer
    Josh Schaeffer is a film editor known for his work on major studio features, including the monster crossover blockbuster "Godzilla vs. Kong."
  • 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: Matt Shively
Triple: [Lopez vs Lopez, starring, Matt Shively]
Generated description
Matt Shively is an American actor best known for his comedic roles on television, including his co-starring role in the sitcom "Lopez vs Lopez."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matt Shively
Target entity description: Matt Shively is an American actor best known for his comedic roles on television, including his co-starring role in the sitcom "Lopez vs Lopez."
  • A. Matt Sherring
    Matt Sherring is a screenwriter best known for writing the action thriller film "Killer Elite."
  • B. Matthew Shoemaker
    Matthew Shoemaker is a Canadian municipal politician serving as the mayor of Sault Ste. Marie, Ontario.
  • C. Brant Daugherty
    Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
  • D. Matt Graver
    Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
  • E. Josh Schaeffer
    Josh Schaeffer is a film editor known for his work on major studio features, including the monster crossover blockbuster "Godzilla vs. Kong."
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509f5ec348190875c8c877e70ba4a completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69e154529dd08190abbfc8d8281a642f completed April 16, 2026, 9:27 p.m.
NEDg Description generation batch_69e17d3060888190b3801272835b939a completed April 17, 2026, 12:22 a.m.
NED2 Entity disambiguation (via description) batch_69e1806bc1048190bcbff6f6d3d7da19 completed April 17, 2026, 12:35 a.m.
Created at: April 6, 2026, 12:29 p.m.