Triple

T3022916
Position Surface form Disambiguated ID Type / Status
Subject Old Yeller E82505 entity
Predicate castMember P1668 FINISHED
Object Kevin Corcoran
Kevin Corcoran was an American child actor best known for his roles in numerous Walt Disney films during the 1950s and 1960s.
E353300 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: Kevin Corcoran | Statement: [Old Yeller, castMember, Kevin Corcoran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kevin Corcoran
Context triple: [Old Yeller, castMember, Kevin Corcoran]
  • A. Kevin O'Connor
    Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
  • B. Max Cullen
    Max Cullen is an Australian character actor known for his extensive work in film, television, and theatre over several decades.
  • C. David Sullivan
    David Sullivan is a British businessman and former pornography and media magnate best known as the co-owner and long-serving chairman of Premier League football club West Ham United.
  • D. Kevin O'Connell
    Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
  • E. Michael Maloney
    Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
  • 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: Kevin Corcoran
Triple: [Old Yeller, castMember, Kevin Corcoran]
Generated description
Kevin Corcoran was an American child actor best known for his roles in numerous Walt Disney films during the 1950s and 1960s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kevin Corcoran
Target entity description: Kevin Corcoran was an American child actor best known for his roles in numerous Walt Disney films during the 1950s and 1960s.
  • A. Kevin O'Connor
    Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
  • B. Max Cullen
    Max Cullen is an Australian character actor known for his extensive work in film, television, and theatre over several decades.
  • C. David Sullivan
    David Sullivan is a British businessman and former pornography and media magnate best known as the co-owner and long-serving chairman of Premier League football club West Ham United.
  • D. Kevin O'Connell
    Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
  • E. Michael Maloney
    Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
  • 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_69ad8b1fb34081908c1b873e2b7273e1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9ab8e0a48190ac79e674abd181cf completed March 8, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b334049c5c8190b870e790795cbec4 completed March 12, 2026, 9:45 p.m.
NEDg Description generation batch_69b337d7daf081909e5112f49a2aa2f2 completed March 12, 2026, 10:02 p.m.
NED2 Entity disambiguation (via description) batch_69b338eb22e4819094e9344aa5decb18 completed March 12, 2026, 10:06 p.m.
Created at: March 8, 2026, 3 p.m.