Triple

T9656970
Position Surface form Disambiguated ID Type / Status
Subject Hawkins E233482 entity
Predicate hasNotableBearer P458 FINISHED
Object Laurel A. Hawkins
Laurel A. Hawkins is an American judge who serves on the Oregon Court of Appeals.
E879655 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: Laurel A. Hawkins | Statement: [Hawkins, hasNotableBearer, Laurel A. Hawkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laurel A. Hawkins
Context triple: [Hawkins, hasNotableBearer, Laurel A. Hawkins]
  • A. Martha D. Saunders
    Martha D. Saunders is an American academic administrator and communications scholar who has served as president of multiple universities, including the University of West Florida.
  • B. Elaine F. Marshall
    Elaine F. Marshall is an American politician and attorney who has served for many years as North Carolina’s Secretary of State, becoming the first woman elected to a statewide executive office in the state.
  • C. Barbara M. Rolph
    Barbara M. Rolph was the woman who sponsored the U.S. Navy heavy cruiser USS San Francisco (CA-38) at its launching ceremony.
  • D. Darla K. Anderson
    Darla K. Anderson is an American film producer best known for her work on several acclaimed Pixar animated features.
  • E. Dona N. Sewell
    Dona N. Sewell is a film editor best known for her work on the comedy movie "Austin Powers: International Man of Mystery."
  • 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: Laurel A. Hawkins
Triple: [Hawkins, hasNotableBearer, Laurel A. Hawkins]
Generated description
Laurel A. Hawkins is an American judge who serves on the Oregon Court of Appeals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Laurel A. Hawkins
Target entity description: Laurel A. Hawkins is an American judge who serves on the Oregon Court of Appeals.
  • A. Martha D. Saunders
    Martha D. Saunders is an American academic administrator and communications scholar who has served as president of multiple universities, including the University of West Florida.
  • B. Elaine F. Marshall
    Elaine F. Marshall is an American politician and attorney who has served for many years as North Carolina’s Secretary of State, becoming the first woman elected to a statewide executive office in the state.
  • C. Barbara M. Rolph
    Barbara M. Rolph was the woman who sponsored the U.S. Navy heavy cruiser USS San Francisco (CA-38) at its launching ceremony.
  • D. Darla K. Anderson
    Darla K. Anderson is an American film producer best known for her work on several acclaimed Pixar animated features.
  • E. Dona N. Sewell
    Dona N. Sewell is a film editor best known for her work on the comedy movie "Austin Powers: International Man of Mystery."
  • 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_69ca848c1ba88190b84b410cd14627fc completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9bdd5c0c8190a6c82a1609454d1b completed April 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69d98801deb8819092a45193078f09b4 completed April 10, 2026, 11:30 p.m.
NEDg Description generation batch_69d98ae8403c81908a229aa06bd0388a completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98ce9ba0c8190a7c62fa670e23705 completed April 10, 2026, 11:51 p.m.
Created at: March 30, 2026, 8:14 p.m.