Triple

T6889434
Position Surface form Disambiguated ID Type / Status
Subject The Abyss E159007 entity
Predicate editedBy P1954 FINISHED
Object Joel Goodman
Joel Goodman is a film editor known for his work on the movie "The Abyss."
E625758 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: Joel Goodman | Statement: [The Abyss, editedBy, Joel Goodman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joel Goodman
Context triple: [The Abyss, editedBy, Joel Goodman]
  • A. Brian Goodman
    Brian Goodman is an American actor and director known for his character roles in film and television, including a notable part in the crime drama series "Rizzoli & Isles."
  • B. Joel Stransky
    Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
  • C. Joel Berez
    Joel Berez is an American businessman best known as a co-founder and early leader of the pioneering interactive fiction game company Infocom.
  • D. Jake Adelstein
    Jake Adelstein is an American journalist and author best known for his memoir "Tokyo Vice," which chronicles his experiences reporting on crime and the yakuza for a major Japanese newspaper.
  • E. Johnny Gandelsman
    Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
  • 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: Joel Goodman
Triple: [The Abyss, editedBy, Joel Goodman]
Generated description
Joel Goodman is a film editor known for his work on the movie "The Abyss."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Joel Goodman
Target entity description: Joel Goodman is a film editor known for his work on the movie "The Abyss."
  • A. Brian Goodman
    Brian Goodman is an American actor and director known for his character roles in film and television, including a notable part in the crime drama series "Rizzoli & Isles."
  • B. Joel Stransky
    Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
  • C. Joel Berez
    Joel Berez is an American businessman best known as a co-founder and early leader of the pioneering interactive fiction game company Infocom.
  • D. Jake Adelstein
    Jake Adelstein is an American journalist and author best known for his memoir "Tokyo Vice," which chronicles his experiences reporting on crime and the yakuza for a major Japanese newspaper.
  • E. Johnny Gandelsman
    Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
  • 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_69c6883568c8819081db6407e892cccc completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d9117c84819093dad7b765337b63 completed March 27, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c742e71bcc81908231a861be47b7db completed March 28, 2026, 2:54 a.m.
NEDg Description generation batch_69c744036378819083a3be5c50b189b2 completed March 28, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69c744eb1cf88190aaf90198d04d4500 completed March 28, 2026, 3:03 a.m.
Created at: March 27, 2026, 2:23 p.m.