Triple
T634500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RCA 1802 microprocessor |
E15992
|
entity |
| Predicate | clockType |
P17358
|
FINISHED |
| Object | external clock input |
—
|
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: external clock input | Statement: [RCA 1802 microprocessor, clockType, external clock input]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clockType Context triple: [RCA 1802 microprocessor, clockType, external clock input]
-
A.
hasClock
Indicates that one entity possesses, contains, or is equipped with a clock.
-
B.
usesClockSystem
Indicates that one entity employs or operates according to the clock or timekeeping system defined or provided by another entity.
-
C.
timeSystem
Indicates a relationship where an entity uses, follows, or is defined within a particular system for measuring or organizing time.
-
D.
timeType
Indicates the specific temporal category or classification associated with a time-related entity or value (e.g., duration, point in time, interval, or recurrence type).
-
E.
clockSpeed
Indicates the operating frequency at which a clock-driven component (such as a processor) performs its cycles or operations over time.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee4ee8481908ad45405e3f3835c |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d0483908190a5ec42a7403c258e |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.