Triple
T712516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Android Dalvik VM |
E14240
|
entity |
| Predicate | registerModel |
P19790
|
FINISHED |
| Object | register-based |
—
|
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: register-based | Statement: [Android Dalvik VM, registerModel, register-based]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registerModel Context triple: [Android Dalvik VM, registerModel, register-based]
-
A.
registrationMode
Indicates the method or process by which something is registered or enrolled.
-
B.
enrollmentModel
Indicates the type or structure of the enrollment relationship that governs how entities (such as users or participants) are registered or associated with a program, course, or service.
-
C.
notableModel
Indicates that an entity is a particularly important, influential, or exemplary instance or version within a broader category or system.
-
D.
register
Indicates that an entity formally records or enrolls another entity or itself in an official system, list, or record.
-
E.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f221b081909fbaa689fb20eb3e |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a77e42e081909a6f2d1bfdc78ef0 |
completed | March 1, 2026, 8:54 p.m. |
Created at: March 1, 2026, 7:36 p.m.