Triple
T4382773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferranti Mark I |
E99166
|
entity |
| Predicate | drumStorageCapacity |
P52985
|
FINISHED |
| Object | several thousand 40-bit words on magnetic drum |
—
|
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: several thousand 40-bit words on magnetic drum | Statement: [Ferranti Mark I, drumStorageCapacity, several thousand 40-bit words on magnetic drum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drumStorageCapacity Context triple: [Ferranti Mark I, drumStorageCapacity, several thousand 40-bit words on magnetic drum]
-
A.
storageCapacity
chosen
Indicates the maximum amount of data or material that a storage entity can hold.
-
B.
dataCapacityDigits
Indicates the number of decimal digits used to represent or specify a data capacity value.
-
C.
hasDrumheadCount
Indicates the number of drumheads associated with or present on a drum or drum-like object.
-
D.
bootCapacity
Indicates the storage volume or carrying capacity available in the boot (trunk) of a vehicle.
-
E.
installedCapacity
Indicates the maximum output or production capability that has been set up or built for a system, facility, or equipment, typically measured under specified conditions.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35262649c8190a724c9835cb7ece6 |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.