Triple

T9501807
Position Surface form Disambiguated ID Type / Status
Subject Ronnie Lott E229158 entity
Predicate hasChild P369 FINISHED
Object Ryan Nece
Ryan Nece is a former American football linebacker who played in the NFL, primarily for the Tampa Bay Buccaneers.
 E805192 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: Ryan Nece | Statement: [Ronnie Lott, hasChild, Ryan Nece]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ryan Nece
Context triple: [Ronnie Lott, hasChild, Ryan Nece]
  • A. Nick Feamster
    Nick Feamster is a computer scientist known for his research in computer networking, Internet measurement, and network security.
  • B. Ryan Brant
    Ryan Brant was an American businessman best known as the founding CEO of video game publisher Take-Two Interactive, the company behind major franchises like Grand Theft Auto.
  • C. Kyle Rote
    Kyle Rote was a former New York Giants star running back and wide receiver who became a prominent American sportscaster and television commentator.
  • D. Lucas Neff
    Lucas Neff is an American actor best known for starring as the lead character Jimmy Chance in the sitcom "Raising Hope."
  • E. Shane Vendrell
    Shane Vendrell is a volatile and morally compromised detective on the TV series "The Shield," known for his loyalty to Vic Mackey and his descent into increasingly tragic and violent choices.
  • 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: Ryan Nece
Triple: [Ronnie Lott, hasChild, Ryan Nece]
Generated description
Ryan Nece is a former American football linebacker who played in the NFL, primarily for the Tampa Bay Buccaneers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ryan Nece
Target entity description: Ryan Nece is a former American football linebacker who played in the NFL, primarily for the Tampa Bay Buccaneers.
  • A. Nick Feamster
    Nick Feamster is a computer scientist known for his research in computer networking, Internet measurement, and network security.
  • B. Ryan Brant
    Ryan Brant was an American businessman best known as the founding CEO of video game publisher Take-Two Interactive, the company behind major franchises like Grand Theft Auto.
  • C. Kyle Rote
    Kyle Rote was a former New York Giants star running back and wide receiver who became a prominent American sportscaster and television commentator.
  • D. Lucas Neff
    Lucas Neff is an American actor best known for starring as the lead character Jimmy Chance in the sitcom "Raising Hope."
  • E. Shane Vendrell
    Shane Vendrell is a volatile and morally compromised detective on the TV series "The Shield," known for his loyalty to Vic Mackey and his descent into increasingly tragic and violent choices.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd983d4b708190a4dfef1246986a26 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c02de448190a2feea16d5461726 completed April 4, 2026, 5:36 p.m.
NEDg Description generation batch_69d14cef4c248190a8dd7b01c9e25a9e completed April 4, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69d14d5dad98819089c49afd3d097c1f completed April 4, 2026, 5:41 p.m.
Created at: March 30, 2026, 7:57 p.m.