Triple
T8436077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SBus |
E199225
|
entity |
| Predicate | slotFormFactor |
P9336
|
FINISHED |
| Object | in-board connector |
—
|
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: in-board connector | Statement: [SBus, slotFormFactor, in-board connector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: slotFormFactor Context triple: [SBus, slotFormFactor, in-board connector]
-
A.
hasFormFactor
chosen
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
B.
deviceShape
Indicates that one entity has the physical form or geometric configuration specified by the other entity.
-
C.
usesFormCharacteristic
Indicates that one entity employs or relies on a particular formal property or structural characteristic of another entity in performing an action or fulfilling a function.
-
D.
slotType
Indicates the classification or category assigned to a particular slot or position within a structure, system, or sequence.
-
E.
touchscreenType
Indicates the specific kind or technology of touchscreen associated with an entity.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:08 p.m.