Triple

T18586928
Position Surface form Disambiguated ID Type / Status
Subject High Resolution Kaon Spectrometer E454258 entity
Predicate abbreviation P43 FINISHED
Object HKS
HKS is a high-resolution magnetic spectrometer designed for precision studies of kaon-induced reactions in nuclear and particle physics experiments.
 E1331448 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: HKS | Statement: [High Resolution Kaon Spectrometer, abbreviation, HKS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HKS
Context triple: [High Resolution Kaon Spectrometer, abbreviation, HKS]
  • A. HKS
    HKS is the Harvard Kennedy School, a leading public policy and public administration graduate school at Harvard University.
  • B. HKS, Inc.
    HKS, Inc. is a global architecture firm known for designing major sports, entertainment, and commercial venues.
  • C. HKS Architects
    HKS Architects is a global architecture firm known for designing large-scale commercial, mixed-use, and hospitality projects.
  • D. HOK Group
    HOK Group is a global design, architecture, engineering, and planning firm known for large-scale commercial, civic, and sports projects.
  • E. Kirkegaard Associates
    Kirkegaard Associates is an acoustical consulting firm renowned for designing the sound environments of prominent performance spaces and concert halls worldwide.
  • 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: HKS
Triple: [High Resolution Kaon Spectrometer, abbreviation, HKS]
Generated description
HKS is a high-resolution magnetic spectrometer designed for precision studies of kaon-induced reactions in nuclear and particle physics experiments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HKS
Target entity description: HKS is a high-resolution magnetic spectrometer designed for precision studies of kaon-induced reactions in nuclear and particle physics experiments.
  • A. HKS
    HKS is the Harvard Kennedy School, a leading public policy and public administration graduate school at Harvard University.
  • B. HKS, Inc.
    HKS, Inc. is a global architecture firm known for designing major sports, entertainment, and commercial venues.
  • C. HKS Architects
    HKS Architects is a global architecture firm known for designing large-scale commercial, mixed-use, and hospitality projects.
  • D. HOK Group
    HOK Group is a global design, architecture, engineering, and planning firm known for large-scale commercial, civic, and sports projects.
  • E. Kirkegaard Associates
    Kirkegaard Associates is an acoustical consulting firm renowned for designing the sound environments of prominent performance spaces and concert halls worldwide.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e545b2f20481908da74447cd08d5bd completed April 19, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a04f8935ea08190936fa5bd6b5ad461 completed May 13, 2026, 10:17 p.m.
NEDg Description generation batch_6a04f96d119481908da5f94feb61bab9 completed May 13, 2026, 10:21 p.m.
NED2 Entity disambiguation (via description) batch_6a04f9dd338881908b300bab7947f736 completed May 13, 2026, 10:23 p.m.
Created at: April 10, 2026, 11:44 a.m.