Triple
T10787751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apollo Guidance Computer |
E254491
|
entity |
| Predicate | fixedMemorySize |
P52984
|
FINISHED |
| Object | 36 kilowords |
—
|
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: 36 kilowords | Statement: [Apollo Guidance Computer, fixedMemorySize, 36 kilowords]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fixedMemorySize Context triple: [Apollo Guidance Computer, fixedMemorySize, 36 kilowords]
-
A.
mainMemorySize
chosen
Indicates the relationship specifying the size or capacity of an entity's main memory.
-
B.
builtInMemoryOf
Indicates that something was constructed as a tribute or commemoration to a particular person, group, or event.
-
C.
stateSizeBytes
Indicates the size of a given state or stateful data in terms of the number of bytes it occupies.
-
D.
maximumVolumeSize
Indicates the largest allowable size or capacity that a volume can have within a given system or context.
-
E.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732d65fcc8190ab5573a861409c56 |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.