Triple
T189076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TI-84 Plus |
E3677
|
entity |
| Predicate | hasRegressionAnalysis |
P5734
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [TI-84 Plus, hasRegressionAnalysis, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegressionAnalysis Context triple: [TI-84 Plus, hasRegressionAnalysis, true]
-
A.
hasStatistics
Indicates that an entity is associated with one or more statistical measures, records, or summaries describing its quantitative properties or performance.
-
B.
analyzes
Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
-
C.
usesComputationMethod
Indicates that an entity performs its processing or decision-making by applying a specified computational method or algorithm.
-
D.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
E.
hasTypeOfExperiment
Indicates that an experiment is associated with or classified under a specific type or category of experiment.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594abeec8190a48f36817e647fcd |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a25738b5108190866fd704fceee18a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.