Triple
T22469522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glen Tullman |
E555456
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Allscripts |
—
|
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: Allscripts | Statement: [Glen Tullman, employer, Allscripts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allscripts Context triple: [Glen Tullman, employer, Allscripts]
-
A.
Allscripts
chosen
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.
-
B.
Cerner
Cerner is a major American health information technology company best known for its electronic health record (EHR) systems and healthcare data solutions.
-
C.
Athenahealth
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.
-
D.
MEDITECH
MEDITECH is a healthcare information technology company best known for providing electronic health record (EHR) and hospital information systems to healthcare organizations.
-
E.
Paradigm4
Paradigm4 is a data analytics software company known for developing the SciDB array database system for large-scale scientific and complex data analysis.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15bdeae9c8190a5b66e540484db37 |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:48 p.m.