Triple
T3665705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CompEd |
E77753
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | CompEd |
E77753
|
NE FINISHED |
How this triple was built (2 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: CompEd | Statement: [CompEd, acronym, CompEd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CompEd Context triple: [CompEd, acronym, CompEd]
-
A.
CompEd
chosen
CompEd is an international ACM SIGCSE conference focused on research and innovation in computing education.
-
B.
OpenLearning
OpenLearning is an online education platform that hosts and delivers massive open online courses (MOOCs) from institutions and educators worldwide.
-
C.
Education Center
The Education Center is a learning facility within the United States Holocaust Memorial Museum that provides educational programs, resources, and interactive experiences to teach about the history and lessons of the Holocaust.
-
D.
LinkedIn Learning
LinkedIn Learning is an online educational platform offering video-based courses in business, technology, and creative skills, integrated with LinkedIn for professional development and career growth.
-
E.
Edu
Edu is a local government area in Kwara State, Nigeria, known for its predominantly Nupe-speaking communities and agrarian economy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc400352081908c16a6a7670eb52a |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4884bd50c8190a334e9aadc734364 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.