Triple

T18300532
Position Surface form Disambiguated ID Type / Status
Subject Ray Tune E438346 entity
Predicate supports P516 FINISHED
Object ASHA
ASHA (Asynchronous Successive Halving Algorithm) is a hyperparameter optimization method that efficiently allocates computational resources by aggressively early-stopping underperforming trials in parallel.
 E1317482 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: ASHA | Statement: [Ray Tune, supports, ASHA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ASHA
Context triple: [Ray Tune, supports, ASHA]
  • A. ASH
    ASH is the ICAO airline designator used to identify Mesa Airlines in international aviation operations.
  • B. ASH
    ASH is the National Rail station code for Ashington railway station in Northumberland, England.
  • C. ASH
    ASH is the leading professional organization in the United States dedicated to the study and treatment of blood disorders and the advancement of hematology research and education.
  • D. ASHT
    ASHT is a professional organization dedicated to advancing the field of hand and upper extremity therapy through education, research, and clinical practice support.
  • E. OASH
    OASH is a division of the U.S. Department of Health and Human Services that provides leadership on national public health policy and oversees key health initiatives and offices.
  • 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: ASHA
Triple: [Ray Tune, supports, ASHA]
Generated description
ASHA (Asynchronous Successive Halving Algorithm) is a hyperparameter optimization method that efficiently allocates computational resources by aggressively early-stopping underperforming trials in parallel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ASHA
Target entity description: ASHA (Asynchronous Successive Halving Algorithm) is a hyperparameter optimization method that efficiently allocates computational resources by aggressively early-stopping underperforming trials in parallel.
  • A. ASH
    ASH is the ICAO airline designator used to identify Mesa Airlines in international aviation operations.
  • B. ASH
    ASH is the National Rail station code for Ashington railway station in Northumberland, England.
  • C. ASH
    ASH is the leading professional organization in the United States dedicated to the study and treatment of blood disorders and the advancement of hematology research and education.
  • D. ASHT
    ASHT is a professional organization dedicated to advancing the field of hand and upper extremity therapy through education, research, and clinical practice support.
  • E. OASH
    OASH is a division of the U.S. Department of Health and Human Services that provides leadership on national public health policy and oversees key health initiatives and offices.
  • 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5017e88cc8190a969eb628ca1b496 completed April 19, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03bb5e1fb481908a0b98ea130eda71 completed May 12, 2026, 11:44 p.m.
NEDg Description generation batch_6a03bdb3fb3c819095192ac49e809f55 completed May 12, 2026, 11:54 p.m.
NED2 Entity disambiguation (via description) batch_6a03c193a0a08190b33d80d45f3ed0f0 completed May 13, 2026, 12:10 a.m.
Created at: April 10, 2026, 10:35 a.m.