Triple
T29389291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PrintAttributes |
E745332
|
entity |
| Predicate | duplexModeType |
P18335
|
FINISHED |
| Object | PrintAttributes.DuplexMode |
—
|
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: PrintAttributes.DuplexMode | Statement: [PrintAttributes, duplexModeType, PrintAttributes.DuplexMode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: duplexModeType Context triple: [PrintAttributes, duplexModeType, PrintAttributes.DuplexMode]
-
A.
duplexMode
chosen
Indicates whether a communication link or device operates in half-duplex or full-duplex mode, defining if data can flow in one or both directions simultaneously.
-
B.
duplexModeInOriginalSpec
Indicates that the duplex (two-sided operation) mode is defined according to the original specification.
-
C.
laterSupportedDuplexMode
Indicates that one entity provided support for duplex mode at a later time than another entity.
-
D.
usesDuplexMethod
Indicates that one entity employs a duplex method, meaning a two-way or bidirectional technique or process, in relation to another entity or context.
-
E.
hasDuplexTunnel
Indicates that there exists a bidirectional (two-way) tunnel connection between two entities.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669d578608190962d35116a01420c |
completed | May 2, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 2:41 p.m.