Triple
T228456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TI-83 Plus |
E4359
|
entity |
| Predicate | hasUserMemory |
P9337
|
FINISHED |
| Object | approximately 24 KB available for user |
—
|
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: approximately 24 KB available for user | Statement: [TI-83 Plus, hasUserMemory, approximately 24 KB available for user]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUserMemory Context triple: [TI-83 Plus, hasUserMemory, approximately 24 KB available for user]
-
A.
hasUser
Indicates that an entity is associated with or linked to a specific user.
-
B.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related service.
-
C.
hasWritingHistory
Indicates that an entity has a recorded history or log of its writing-related actions, changes, or authored content over time.
-
D.
usedBefore
Indicates that one entity was utilized or applied prior to the use or occurrence of another entity.
-
E.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d10ac248190a98dedabf5358668 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b5877588190af694d060377f027 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d0ec71081908478c800be4f7bb0 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.