Triple

T13349732
Position Surface form Disambiguated ID Type / Status
Subject Grace Hopper E318039 entity
Predicate givenName P17 FINISHED
Object Grace
Grace is the first name of Grace Hopper, a pioneering American computer scientist and U.S. Navy rear admiral known for her work on early programming languages and compilers.
E295685 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: Grace | Statement: [Grace Hopper, givenName, Grace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grace
Context triple: [Grace Hopper, givenName, Grace]
  • A. Grace
    "Grace" is a British crime drama television series starring John Simm as Detective Superintendent Roy Grace, adapted from Peter James's bestselling novels.
  • B. Grace
    Grace is Jeff Buckley’s acclaimed 1994 debut studio album, celebrated for its emotive vocals, eclectic songwriting, and enduring influence on alternative rock.
  • C. Grace
    Grace is the NATO reporting name for the Aichi B7A, a Japanese World War II carrier-based torpedo-dive bomber aircraft.
  • D. Grace
    Grace is a cybernetically enhanced human soldier from the future who serves as one of the main protagonists in the film "Terminator: Dark Fate."
  • E. Grace
    Grace is a central character in the 1969 film "The Slave," notable for her role within the movie’s historical adventure narrative.
  • 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: Grace
Triple: [Grace Hopper, givenName, Grace]
Generated description
Grace is the first name of Grace Hopper, a pioneering American computer scientist and U.S. Navy rear admiral known for her work on early programming languages and compilers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Grace
Target entity description: Grace is the first name of Grace Hopper, a pioneering American computer scientist and U.S. Navy rear admiral known for her work on early programming languages and compilers.
  • A. Grace
    Grace is a common English surname of Latin origin, often associated with elegance and divine favor.
  • B. Grace chosen
    Grace is a feminine given name of Latin origin meaning "grace" or "favor," often associated with elegance and kindness.
  • C. Grace
    Grace is the NATO reporting name for the Aichi B7A, a Japanese World War II carrier-based torpedo-dive bomber aircraft.
  • D. Grace
    Grace is a cybernetically enhanced human soldier from the future who serves as one of the main protagonists in the film "Terminator: Dark Fate."
  • E. Grace
    Grace is a skilled and enigmatic thief who becomes entangled with Ethan Hunt and the IMF team in the action film "Mission: Impossible – Dead Reckoning Part One."
  • F. None of above.

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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8b28e48190a23194e03a74b41b completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f47fd7c8190b8d98a181acd7710 completed May 3, 2026, 10:11 a.m.
NEDg Description generation batch_69f7204b6f108190bca6a0140620e03e completed May 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_69f720fbf0bc81908c68cf2844938e45 completed May 3, 2026, 10:18 a.m.
Created at: April 9, 2026, 9:31 p.m.