Triple
T17005746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pioneer ACO Model |
E412564
|
entity |
| Predicate | usesBenchmark |
P55279
|
FINISHED |
| Object | historical spending trends |
—
|
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: historical spending trends | Statement: [Pioneer ACO Model, usesBenchmark, historical spending trends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBenchmark Context triple: [Pioneer ACO Model, usesBenchmark, historical spending trends]
-
A.
benchmarkFor
Indicates that one entity serves as a standard or reference point against which the performance, quality, or characteristics of another entity are measured or evaluated.
-
B.
numberOfBenchmarksUsed
Indicates the quantity of distinct benchmarks that are utilized in a given context or evaluation.
-
C.
benchmarkVariant
Indicates that one entity is a specific version or variation of another entity used for benchmarking or performance comparison.
-
D.
primaryBenchmarkProvider
Indicates that one entity serves as the main or default source of benchmark data or performance standards for another entity.
-
E.
usesBaseline
chosen
Indicates that one entity relies on or applies another entity as a reference baseline for comparison, measurement, or evaluation.
- F. None of above.
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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d3831268819089286053a5acf653 |
completed | April 18, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.