Triple
T38571692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 14 Plus |
E929291
|
entity |
| Predicate | concurrentModels |
P164281
|
FINISHED |
| Object | iPhone 14 |
—
|
NE NERFINISHED |
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: iPhone 14 | Statement: [iPhone 14 Plus, concurrentModels, iPhone 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concurrentModels Context triple: [iPhone 14 Plus, concurrentModels, iPhone 14]
-
A.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
B.
supportsConcurrentModelExecution
Indicates that one entity enables or allows multiple models to be executed at the same time without mutual interference.
-
C.
numberOfModels
Indicates the quantity or count of models associated with a given entity or context.
-
D.
concurrentProductWith
chosen
Indicates that two or more products are available, used, or occur at the same time within the same context or transaction.
-
E.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.