Triple
T19585687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Todd Park |
E490099
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Athenahealth |
—
|
NE NERFINISHED |
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: Athenahealth | Statement: [Todd Park, employer, Athenahealth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Athenahealth Context triple: [Todd Park, employer, Athenahealth]
-
A.
Athenahealth
chosen
Athenahealth is a U.S.-based healthcare technology company that provides cloud-based electronic health record, practice management, and revenue cycle management solutions for medical practices and health systems.
-
B.
Amwell
Amwell is a village in Hertfordshire, England, known for its historic countryside setting and proximity to landmarks such as Scott’s Grotto.
-
C.
Flatiron Health
Flatiron Health is a healthcare technology company that specializes in using real-world oncology data and software to improve cancer care and research.
-
D.
Paradigm4
Paradigm4 is a data analytics software company known for developing the SciDB array database system for large-scale scientific and complex data analysis.
-
E.
Allscripts
Allscripts is a healthcare information technology company known for providing electronic health record (EHR), practice management, and related software solutions to hospitals and physician practices.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e640513134819082cf233fa3dcc911 |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.