Triple
T26408770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RadioGatún |
E663900
|
entity |
| Predicate | hasStateSize |
P180002
|
FINISHED |
| Object | large internal state |
—
|
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: large internal state | Statement: [RadioGatún, hasStateSize, large internal state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStateSize Context triple: [RadioGatún, hasStateSize, large internal state]
-
A.
hasStateSizeBits
Indicates the number of bits used to represent the size of a state in a system or data structure.
-
B.
stateSize
Indicates the relative or absolute physical extent or dimensions of a state, such as its area or population size.
-
C.
hasSize
Indicates that one entity possesses a particular physical magnitude or extent, such as length, volume, or overall dimensions.
-
D.
stateSizeBytes
Indicates the size of a given state or stateful data in terms of the number of bytes it occupies.
-
E.
hasTotalSize
Indicates that an entity possesses or is associated with a specific overall size or aggregate measurement.
- 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 26, 2026, 11:36 p.m.