Triple

T1809574
Position Surface form Disambiguated ID Type / Status
Subject Troop Zero E40299 entity
Predicate editor P1954 FINISHED
Object Jonathan Lucas
Jonathan Lucas is a film editor known for his work on the feature film "Troop Zero."
E210986 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: Jonathan Lucas | Statement: [Troop Zero, editor, Jonathan Lucas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan Lucas
Context triple: [Troop Zero, editor, Jonathan Lucas]
  • A. John Paul Lucas
    John Paul Lucas is an American architect best known for co-designing the Korean War Veterans Memorial in Washington, D.C.
  • B. Jonathan Lisco
    Jonathan Lisco is an American television writer, producer, and showrunner known for his work on series such as Animal Kingdom, Halt and Catch Fire, and Jack & Bobby.
  • C. Jason Hudson
    Jason Hudson was the brother of singer and actress Jennifer Hudson, tragically murdered in a widely publicized 2008 family shooting in Chicago.
  • D. Michael Jenkins
    Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
  • E. Jeremy Jacobs
    Jeremy Jacobs is an American billionaire businessman and longtime owner of the NHL’s Boston Bruins, known for his influential role in professional hockey and sports venue management.
  • 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: Jonathan Lucas
Triple: [Troop Zero, editor, Jonathan Lucas]
Generated description
Jonathan Lucas is a film editor known for his work on the feature film "Troop Zero."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jonathan Lucas
Target entity description: Jonathan Lucas is a film editor known for his work on the feature film "Troop Zero."
  • A. John Paul Lucas
    John Paul Lucas is an American architect best known for co-designing the Korean War Veterans Memorial in Washington, D.C.
  • B. Jonathan Lisco
    Jonathan Lisco is an American television writer, producer, and showrunner known for his work on series such as Animal Kingdom, Halt and Catch Fire, and Jack & Bobby.
  • C. Jason Hudson
    Jason Hudson was the brother of singer and actress Jennifer Hudson, tragically murdered in a widely publicized 2008 family shooting in Chicago.
  • D. Michael Jenkins
    Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
  • E. Jeremy Jacobs
    Jeremy Jacobs is an American billionaire businessman and longtime owner of the NHL’s Boston Bruins, known for his influential role in professional hockey and sports venue management.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65c310d88190bfd9c27fa238e648 completed March 6, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69adead39c208190aa3aaf793c7e3224 completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adeb1049dc8190bbf9aa6ad5ad1ad9 completed March 8, 2026, 9:33 p.m.
NED2 Entity disambiguation (via description) batch_69adeb8d6c948190a28963faa04b6883 completed March 8, 2026, 9:35 p.m.
Created at: March 4, 2026, 7:32 p.m.