Triple
T2441895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | @TJOshie77 |
E53294
|
entity |
| Predicate | accountType |
P38507
|
FINISHED |
| Object | official account |
—
|
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: official account | Statement: [@TJOshie77, accountType, official account]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accountType Context triple: [@TJOshie77, accountType, official account]
-
A.
supportsAccountType
Indicates that one entity is compatible with, or able to operate for, a specified type or category of account.
-
B.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
-
C.
credentialType
Indicates the specific kind or category of credential associated with an entity or relationship.
-
D.
hasBankType
Indicates that an entity is associated with or classified by a particular type or category of bank.
-
E.
organizationType
Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcabf477081908512df63ac1a6414 |
completed | March 7, 2026, 6:50 a.m. |
| PD | Predicate disambiguation | batch_69abc5ad8e588190b97c4cd7cf575043 |
completed | March 7, 2026, 6:29 a.m. |
| PDg | Predicate description generation | batch_69abcabe646c8190855d13b5dff07b97 |
completed | March 7, 2026, 6:50 a.m. |
Created at: March 6, 2026, 9:43 p.m.