Triple
T26966671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BPP |
E679189
|
entity |
| Predicate | decisionProblemType |
P132452
|
FINISHED |
| Object | language recognition |
—
|
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: language recognition | Statement: [BPP, decisionProblemType, language recognition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decisionProblemType Context triple: [BPP, decisionProblemType, language recognition]
-
A.
decisionProblem
chosen
Indicates that the subject is a computational problem for which the task is to decide, with a yes/no answer, whether given inputs satisfy a specified condition.
-
B.
decisionType
Indicates the specific category or nature of a decision associated with an entity or event.
-
C.
decisionMakingTool
Indicates that an entity functions as a tool or system used to support, structure, or carry out decision-making processes for another entity.
-
D.
decisionMakerType
Indicates the role or category of entity responsible for making a particular decision.
-
E.
decisionMakingModel
Indicates a relationship where an entity uses or is associated with a specific model or framework for making decisions.
- 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 6:36 a.m.