Triple
T35053645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emotion Engine |
E1011399
|
entity |
| Predicate | vectorUnitType |
P182054
|
FINISHED |
| Object | SIMD vector coprocessor |
—
|
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: SIMD vector coprocessor | Statement: [Emotion Engine, vectorUnitType, SIMD vector coprocessor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vectorUnitType Context triple: [Emotion Engine, vectorUnitType, SIMD vector coprocessor]
-
A.
vectorUnit
chosen
Indicates that an entity functions as a vector processing unit or is associated with vector-based computation or operations.
-
B.
vectorType
Indicates that one entity is classified as the type or category of vector associated with another entity.
-
C.
typeOfUnit
Indicates that one entity specifies the kind or category of measurement unit that the other entity belongs to.
-
D.
vector
Indicates that one entity is a vector associated with, representing, or characterizing another entity (such as a quantity with magnitude and direction, or a carrier/representative of something).
-
E.
typeOfUnitCommanded
Indicates the specific type or category of military or organizational unit that an entity is in command of.
- 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_69f76dcfdda48190b1ebae5da8b54f12 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.