Triple

T20699630
Position Surface form Disambiguated ID Type / Status
Subject Just Because E508743 entity
Predicate writer P1360 FINISHED
Object Michael O’Hara
Michael O’Hara is a screenwriter best known for his work on the film "Just Because."
 E1507249 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: Michael O’Hara | Statement: [Just Because, writer, Michael O’Hara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael O’Hara
Context triple: [Just Because, writer, Michael O’Hara]
  • A. Michael O'Hara
    Michael O'Hara is the naive Irish sailor protagonist of the 1947 film noir "The Lady from Shanghai," whose involvement with a mysterious woman draws him into a web of murder and betrayal.
  • B. Michael O'Hara
    Michael O'Hara was an American attorney best known for being one of the later husbands of Hungarian-American socialite and actress Zsa Zsa Gabor.
  • C. Roger O'Connor
    Roger O'Connor was an Irish nationalist and writer known for his radical political views in the late 18th and early 19th centuries.
  • D. Hugh McDermott
    Hugh McDermott was a Scottish actor known for his supporting roles in British films of the 1930s and 1940s.
  • E. John Doherty
    John Doherty is known as the husband of American actress Michael Learned, famed for her role as Olivia Walton on the television series "The Waltons."
  • 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: Michael O’Hara
Triple: [Just Because, writer, Michael O’Hara]
Generated description
Michael O’Hara is a screenwriter best known for his work on the film "Just Because."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael O’Hara
Target entity description: Michael O’Hara is a screenwriter best known for his work on the film "Just Because."
  • A. Michael O'Hara
    Michael O'Hara is the naive Irish sailor protagonist of the 1947 film noir "The Lady from Shanghai," whose involvement with a mysterious woman draws him into a web of murder and betrayal.
  • B. Michael O'Hara
    Michael O'Hara was an American attorney best known for being one of the later husbands of Hungarian-American socialite and actress Zsa Zsa Gabor.
  • C. Roger O'Connor
    Roger O'Connor was an Irish nationalist and writer known for his radical political views in the late 18th and early 19th centuries.
  • D. Hugh McDermott
    Hugh McDermott was a Scottish actor known for his supporting roles in British films of the 1930s and 1940s.
  • E. John Doherty
    John Doherty is known as the husband of American actress Michael Learned, famed for her role as Olivia Walton on the television series "The Waltons."
  • 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_69e0b4c2b2a481909e31e9cb8f81ab55 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6c18a77308190b7c2517d82a145cd completed April 21, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a59ec05c081909af30673439872ce completed May 18, 2026, 12:14 a.m.
NEDg Description generation batch_6a0a5b0d434481909d2d011c2449bf69 completed May 18, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a0a5ba4fb5c8190994938f704603690 completed May 18, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:11 p.m.