Triple
T201267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Department of Education |
E4508
|
entity |
| Predicate | overseesProgram |
P86
|
FINISHED |
| Object |
Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP)
Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) is a U.S. federal initiative that supports low-income and underserved students in preparing for and succeeding in postsecondary education through long-term, cohort-based services and scholarships.
|
E25564
|
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: Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) | Statement: [United States Department of Education, overseesProgram, Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) Context triple: [United States Department of Education, overseesProgram, Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP)]
-
A.
Research Experiences for Undergraduates (REU)
Research Experiences for Undergraduates (REU) is a U.S. program that funds intensive, mentored research opportunities for undergraduate students across a wide range of scientific and engineering disciplines.
-
B.
Advanced Technological Education (ATE)
Advanced Technological Education (ATE) is a National Science Foundation program that supports the education and training of technicians in advanced technology fields through partnerships between two-year colleges, industry, and other educational institutions.
-
C.
Consortium on Financing Higher Education
The Consortium on Financing Higher Education is an organization of highly selective, private colleges and universities in the United States that collaborates on issues related to financial aid, affordability, and access to higher education.
-
D.
Grace Hopper College
Grace Hopper College is one of Yale University's undergraduate residential colleges, named after computer science pioneer Rear Admiral Grace Hopper.
-
E.
BEA Program
The BEA Program is a U.S. Treasury initiative that provides financial incentives to banks to increase lending, investment, and financial services in economically distressed communities.
- 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: Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) Triple: [United States Department of Education, overseesProgram, Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP)]
Generated description
Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) is a U.S. federal initiative that supports low-income and underserved students in preparing for and succeeding in postsecondary education through long-term, cohort-based services and scholarships.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) Target entity description: Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) is a U.S. federal initiative that supports low-income and underserved students in preparing for and succeeding in postsecondary education through long-term, cohort-based services and scholarships.
-
A.
Research Experiences for Undergraduates (REU)
Research Experiences for Undergraduates (REU) is a U.S. program that funds intensive, mentored research opportunities for undergraduate students across a wide range of scientific and engineering disciplines.
-
B.
Advanced Technological Education (ATE)
Advanced Technological Education (ATE) is a National Science Foundation program that supports the education and training of technicians in advanced technology fields through partnerships between two-year colleges, industry, and other educational institutions.
-
C.
Consortium on Financing Higher Education
The Consortium on Financing Higher Education is an organization of highly selective, private colleges and universities in the United States that collaborates on issues related to financial aid, affordability, and access to higher education.
-
D.
Grace Hopper College
Grace Hopper College is one of Yale University's undergraduate residential colleges, named after computer science pioneer Rear Admiral Grace Hopper.
-
E.
BEA Program
The BEA Program is a U.S. Treasury initiative that provides financial incentives to banks to increase lending, investment, and financial services in economically distressed communities.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25be5a6d081909723b23a6361d6ea |
completed | Feb. 28, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a323308b748190aea2e7dff74e7202 |
completed | Feb. 28, 2026, 5:17 p.m. |
| NEDg | Description generation | batch_69a323be36ac8190949a2c6f08c9a215 |
completed | Feb. 28, 2026, 5:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3241f3cd08190a77ef4307a0e6dd0 |
completed | Feb. 28, 2026, 5:21 p.m. |
Created at: Feb. 28, 2026, 2:51 a.m.