Triple

T5228720
Position Surface form Disambiguated ID Type / Status
Subject Roots E118055 entity
Predicate director P255 FINISHED
Object John Erman
John Erman was an American television and film director best known for his work on acclaimed TV miniseries and dramas from the 1970s onward.
 E505943 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: John Erman | Statement: [Roots, director, John Erman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Erman
Context triple: [Roots, director, John Erman]
  • A. Rex Hanson
    Rex Hanson is a wealthy, arrogant antagonist in the comedy film "Horrible Bosses 2," known for scheming against the main characters.
  • B. Robert Mann
    Robert Mann was a 19th-century American man best known as the son of influential education reformer Horace Mann.
  • C. Joe Morse
    Joe Morse is the morally conflicted lawyer protagonist of the 1948 film noir "Force of Evil," whose involvement with racketeering drives the movie’s exploration of corruption and conscience.
  • D. Jeff Newton
    Jeff Newton is an American professional basketball player best known for his standout career in Japan's B.League, where he became a key frontcourt star and multiple-time champion.
  • E. Bryan DeWitt
    Bryan DeWitt is a person notable enough to be recognized as a bearer of the De Witt surname.
  • 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: John Erman
Triple: [Roots, director, John Erman]
Generated description
John Erman was an American television and film director best known for his work on acclaimed TV miniseries and dramas from the 1970s onward.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Erman
Target entity description: John Erman was an American television and film director best known for his work on acclaimed TV miniseries and dramas from the 1970s onward.
  • A. Rex Hanson
    Rex Hanson is a wealthy, arrogant antagonist in the comedy film "Horrible Bosses 2," known for scheming against the main characters.
  • B. Robert Mann
    Robert Mann was a 19th-century American man best known as the son of influential education reformer Horace Mann.
  • C. Joe Morse
    Joe Morse is the morally conflicted lawyer protagonist of the 1948 film noir "Force of Evil," whose involvement with racketeering drives the movie’s exploration of corruption and conscience.
  • D. Jeff Newton
    Jeff Newton is an American professional basketball player best known for his standout career in Japan's B.League, where he became a key frontcourt star and multiple-time champion.
  • E. Bryan DeWitt
    Bryan DeWitt is a person notable enough to be recognized as a bearer of the De Witt surname.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7adee36881909b034b8735db9d67 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef80ca924819095bcc729feb0e464 completed March 21, 2026, 7:57 p.m.
NEDg Description generation batch_69bef8996a208190b9b84b297434c549 completed March 21, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_69bef935c2288190b2c66e25b8f065bd completed March 21, 2026, 8:01 p.m.
Created at: March 20, 2026, 1:48 p.m.