Triple

T12681325
Position Surface form Disambiguated ID Type / Status
Subject CuSP CubeSat E302953 entity
Predicate acronym P43 FINISHED
Object CuSP
CuSP is a small CubeSat spacecraft designed to study space weather and the interplanetary environment.
 E997187 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: CuSP | Statement: [CuSP CubeSat, acronym, CuSP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CuSP
Context triple: [CuSP CubeSat, acronym, CuSP]
  • A. CUCS
    CUCS is a health sciences university center of the University of Guadalajara in Mexico, focused on education and research in medical and related disciplines.
  • B. CPS
    CPS is the principal public agency in England and Wales responsible for prosecuting criminal cases investigated by the police.
  • C. CPS
    CPS is the commonly used abbreviation for Chicago Public Schools, the third-largest school district in the United States.
  • D. CPS
    CPS is the three-letter IATA airport code for St. Louis Downtown Airport, a regional airport serving the St. Louis metropolitan area.
  • E. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • 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: CuSP
Triple: [CuSP CubeSat, acronym, CuSP]
Generated description
CuSP is a small CubeSat spacecraft designed to study space weather and the interplanetary environment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CuSP
Target entity description: CuSP is a small CubeSat spacecraft designed to study space weather and the interplanetary environment.
  • A. CUCS
    CUCS is a health sciences university center of the University of Guadalajara in Mexico, focused on education and research in medical and related disciplines.
  • B. CPS
    CPS is the principal public agency in England and Wales responsible for prosecuting criminal cases investigated by the police.
  • C. CPS
    CPS is the commonly used abbreviation for Chicago Public Schools, the third-largest school district in the United States.
  • D. CPS
    CPS is the three-letter IATA airport code for St. Louis Downtown Airport, a regional airport serving the St. Louis metropolitan area.
  • E. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b32dbc81908101fc5f07e26ed3 completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a54b008190b02f9585d6c6ff77 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f67285019c8190be831d3f72cf121f completed May 2, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_69f67323a724819092425cdb3a070b96 completed May 2, 2026, 9:56 p.m.
Created at: April 9, 2026, 5:21 p.m.