Triple
T8284048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RV128I |
E193747
|
entity |
| Predicate | numericTypeFocus |
P82496
|
FINISHED |
| Object | integer operations with 128-bit word size |
—
|
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: integer operations with 128-bit word size | Statement: [RV128I, numericTypeFocus, integer operations with 128-bit word size]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numericTypeFocus Context triple: [RV128I, numericTypeFocus, integer operations with 128-bit word size]
-
A.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
C.
numericalProperty
Indicates that an entity is associated with a specific numeric value or measurable quantity.
-
D.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
E.
floatType
Indicates that an entity has a specific floating-point data type or is categorized as a floating-point numeric value.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7ad0535081908bb234cfc0e32b32 |
completed | March 31, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:52 p.m.