Triple
T14161897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Carolina Commission on Higher Education |
E350967
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
SC CHE
SC CHE is the state agency responsible for coordinating and overseeing public higher education policy and planning in South Carolina.
|
E1084218
|
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: SC CHE | Statement: [South Carolina Commission on Higher Education, abbreviation, SC CHE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SC CHE Context triple: [South Carolina Commission on Higher Education, abbreviation, SC CHE]
-
A.
CHED
CHED is the commonly used abbreviation for the Division of Chemical Education, a professional organization focused on advancing the teaching and learning of chemistry.
-
B.
CHE
CHE is the three-letter ISO 3166-1 alpha-3 country code for Switzerland.
-
C.
CHES
CHES (Cryptographic Hardware and Embedded Systems) is a leading annual conference focused on the design and analysis of cryptographic hardware and security in embedded systems.
-
D.
SCS
SCS is Carnegie Mellon University's renowned School of Computer Science, recognized globally for pioneering research and education in computing and related fields.
-
E.
SCHA
SCHA is the stock ticker symbol under which Schibsted, a Nordic media and online marketplace company, is traded on financial markets.
- 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: SC CHE Triple: [South Carolina Commission on Higher Education, abbreviation, SC CHE]
Generated description
SC CHE is the state agency responsible for coordinating and overseeing public higher education policy and planning in South Carolina.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SC CHE Target entity description: SC CHE is the state agency responsible for coordinating and overseeing public higher education policy and planning in South Carolina.
-
A.
CHED
CHED is the commonly used abbreviation for the Division of Chemical Education, a professional organization focused on advancing the teaching and learning of chemistry.
-
B.
CHE
CHE is the three-letter ISO 3166-1 alpha-3 country code for Switzerland.
-
C.
CHES
CHES (Cryptographic Hardware and Embedded Systems) is a leading annual conference focused on the design and analysis of cryptographic hardware and security in embedded systems.
-
D.
SCS
SCS is Carnegie Mellon University's renowned School of Computer Science, recognized globally for pioneering research and education in computing and related fields.
-
E.
SCHA
SCHA is the stock ticker symbol under which Schibsted, a Nordic media and online marketplace company, is traded on financial markets.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de613a4a2081908fd51bf4b4d82b6c |
completed | April 14, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f166988190a96d01fb4bd1438e |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fd05f31d9c81908b12befa499fae08 |
completed | May 7, 2026, 9:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd068196fc8190b0c5620c754d2a5c |
completed | May 7, 2026, 9:39 p.m. |
Created at: April 10, 2026, 12:59 a.m.