Triple
T11351608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Desktop Bus port |
E268850
|
entity |
| Predicate | busTopology |
P12678
|
FINISHED |
| Object | linear daisy-chain |
—
|
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: linear daisy-chain | Statement: [Apple Desktop Bus port, busTopology, linear daisy-chain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: busTopology Context triple: [Apple Desktop Bus port, busTopology, linear daisy-chain]
-
A.
usesTopology
Indicates that one entity employs, is based on, or operates according to a particular topology defined or provided by another entity.
-
B.
typicalTopology
Indicates the usual or most common network or structural arrangement that characterizes how the related entities are organized or interconnected.
-
C.
hasTopology
chosen
Indicates that one entity possesses, exhibits, or is characterized by a particular structural or spatial configuration defined by the other entity.
-
D.
isTopological
Indicates that something possesses the properties or structure required to be considered a topology in the relevant mathematical or spatial context.
-
E.
networkModel
Indicates a relationship where an entity is represented or organized according to a specific network-based structure or framework.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.