Triple
T5501447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuance Communications |
E144337
|
entity |
| Predicate | providesSolutionFor |
P65108
|
FINISHED |
| Object | healthcare |
—
|
LITERAL 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: healthcare | Statement: [Nuance Communications, providesSolutionFor, healthcare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesSolutionFor Context triple: [Nuance Communications, providesSolutionFor, healthcare]
-
A.
solutionType
Indicates the specific category or kind of solution associated with an entity or problem.
-
B.
basedOnSolutionOf
Indicates that one entity is derived, developed, or constructed using the solution or outcome produced by another entity.
-
C.
isSolutionOf
Indicates that one entity is a correct answer or satisfies the conditions of a given problem, equation, or task.
-
D.
admitsSolution
Indicates that a problem, system, or situation allows for or possesses at least one valid solution.
-
E.
solved
Indicates that one entity has successfully found a solution or answer to a problem, task, or challenge involving another entity.
- F. None of above. chosen
Provenance (4 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_69c008f5a2748190bce7a39aabf87a6d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f0a512c81908f077378917e5879 |
completed | March 22, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69c01b052f3c81909f71c6add0f35a6f |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:32 p.m.