Triple
T29738946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM High Level Assembler |
E752542
|
entity |
| Predicate | supportsDataEncoding |
P33682
|
FINISHED |
| Object | EBCDIC |
—
|
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: EBCDIC | Statement: [IBM High Level Assembler, supportsDataEncoding, EBCDIC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDataEncoding Context triple: [IBM High Level Assembler, supportsDataEncoding, EBCDIC]
-
A.
dataEncodingMethod
chosen
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
-
B.
supportsDataFrom
Indicates that one entity provides, validates, or underpins the data used or referenced by another entity.
-
C.
usesEncoder
Indicates that one entity employs or relies on an encoder component or mechanism to perform its function or process data.
-
D.
usesDifferentialEncoding
Indicates that one entity applies differential encoding techniques to represent or transmit information relative to changes rather than absolute values.
-
E.
usesEncodingRules
Indicates that one entity applies or conforms to a specified set of encoding rules when representing or transforming information.
- 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_69f0d62b064081908c1ae61cd68fb139 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 28, 2026, 7:47 p.m.