Triple
T29390433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UHS-I |
E745355
|
entity |
| Predicate | physicalPins |
P168145
|
FINISHED |
| Object | uses existing SD card pin layout |
—
|
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: uses existing SD card pin layout | Statement: [UHS-I, physicalPins, uses existing SD card pin layout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: physicalPins Context triple: [UHS-I, physicalPins, uses existing SD card pin layout]
-
A.
dataPinCount
Indicates the number of data pins associated with or used by an entity in a given context.
-
B.
pins
Indicates that one entity fastens, secures, or immobilizes another entity in place, typically using a pin-like object or mechanism.
-
C.
pinCount
Indicates the number of pins associated with or assigned to a given entity.
-
D.
powerPinCount
Indicates the number of power-related pins associated with an electronic component or connector.
-
E.
hasNumberOfPins
Indicates that an entity is associated with a specific count of pins it possesses or uses.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 28, 2026, 2:42 p.m.