Triple
T4442481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mruby |
E96204
|
entity |
| Predicate | garbageCollectorType |
P16210
|
FINISHED |
| Object | mark-and-sweep |
—
|
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: mark-and-sweep | Statement: [mruby, garbageCollectorType, mark-and-sweep]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: garbageCollectorType Context triple: [mruby, garbageCollectorType, mark-and-sweep]
-
A.
usesGarbageCollectorType
chosen
Indicates that one entity employs or is configured to employ a specific type of garbage collection mechanism or strategy associated with another entity.
-
B.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
-
C.
clearingSystem
Indicates that one entity functions as the financial clearing mechanism or infrastructure used to settle transactions for another entity.
-
D.
decompositionType
Indicates the specific way in which a whole is broken down into its constituent parts or components.
-
E.
acceleratorType
Indicates the kind or category of accelerator associated with or used by 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355aef21c819088f168a23f1933a6 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.