Triple

T8336044
Position Surface form Disambiguated ID Type / Status
Subject Steven Mackintosh E195787 entity
Predicate notableWork P4 FINISHED
Object Good
Good is a British television drama film exploring moral dilemmas in 1930s Nazi Germany, adapted from C. P. Taylor’s stage play of the same name.
 E724883 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: Good | Statement: [Steven Mackintosh, notableWork, Good]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Good
Context triple: [Steven Mackintosh, notableWork, Good]
  • A. Good
    Good is a surname of English origin borne by various individuals, including historical figures such as Sarah Good of Salem witch trials notoriety.
  • B. Gutes
    The Gutes were the North Germanic inhabitants of the Baltic island of Gotland, known for their distinct Gutnish language and extensive Viking Age trade networks.
  • C. Good Stuff
    Good Stuff is likely a component or segment of the television program "Kaleidoscope," possibly a recurring feature or themed section within the show.
  • D. Feels Good
    "Feels Good" is a 1990 new jack swing and R&B hit single by Tony! Toni! Toné! that became one of the group's signature songs.
  • E. For Good
    "For Good" is a poignant duet from the Broadway musical Wicked that reflects on the lasting impact of meaningful relationships and personal change.
  • 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: Good
Triple: [Steven Mackintosh, notableWork, Good]
Generated description
Good is a British television drama film exploring moral dilemmas in 1930s Nazi Germany, adapted from C. P. Taylor’s stage play of the same name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Good
Target entity description: Good is a British television drama film exploring moral dilemmas in 1930s Nazi Germany, adapted from C. P. Taylor’s stage play of the same name.
  • A. Good
    Good is a surname of English origin borne by various individuals, including historical figures such as Sarah Good of Salem witch trials notoriety.
  • B. Gutes
    The Gutes were the North Germanic inhabitants of the Baltic island of Gotland, known for their distinct Gutnish language and extensive Viking Age trade networks.
  • C. Good Stuff
    Good Stuff is likely a component or segment of the television program "Kaleidoscope," possibly a recurring feature or themed section within the show.
  • D. Feels Good
    "Feels Good" is a 1990 new jack swing and R&B hit single by Tony! Toni! Toné! that became one of the group's signature songs.
  • E. For Good
    "For Good" is a poignant duet from the Broadway musical Wicked that reflects on the lasting impact of meaningful relationships and personal change.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd3fc80819097b326119107ad4d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95d9b92c8190b1eb0e64aa7ea59e completed April 1, 2026, 10:02 p.m.
NEDg Description generation batch_69cda342c10881908ebafc7853815424 completed April 1, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_69cdab736f208190a90bd4344b21a22c completed April 1, 2026, 11:34 p.m.
Created at: March 30, 2026, 5:57 p.m.