Triple
T11550858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warnock algorithm |
E273884
|
entity |
| Predicate | classificationTest |
P100090
|
FINISHED |
| Object | primitive completely outside region |
—
|
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: primitive completely outside region | Statement: [Warnock algorithm, classificationTest, primitive completely outside region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classificationTest Context triple: [Warnock algorithm, classificationTest, primitive completely outside region]
-
A.
classificationIssue
Indicates that there is a problem, ambiguity, or error in how something has been categorized or assigned to a class or type.
-
B.
classificationConsensus
Indicates that multiple agents or sources agree on the same classification or category assignment for a given entity or item.
-
C.
outputClassification
Indicates how a given output is categorized or labeled according to a specified classification scheme.
-
D.
classificationApproach
Indicates the method or strategy used to categorize or assign entities into classes or groups.
-
E.
classificationProblem
Indicates a relationship where a task involves assigning items or instances to one of several predefined categories or classes based on their features.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a83f1e88190aabf11a4c8a6c9e5 |
completed | April 10, 2026, 5:28 a.m. |
| PD | Predicate disambiguation | batch_69d8087e57b48190a4c253dc0210f9d4 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822f00a088190ac6b48e45e743899 |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:37 p.m.