Triple
T701095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ID.me |
E13999
|
entity |
| Predicate | authenticationType |
P18412
|
FINISHED |
| Object | multi‑factor authentication |
—
|
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: multi‑factor authentication | Statement: [ID.me, authenticationType, multi‑factor authentication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authenticationType Context triple: [ID.me, authenticationType, multi‑factor authentication]
-
A.
credentialType
Indicates the specific kind or category of credential associated with an entity or relationship.
-
B.
securityType
Indicates the classification or category of security associated with an entity, such as the type of financial instrument, protection mechanism, or access control applied.
-
C.
permitType
Indicates the specific category or kind of permit associated with an entity or activity.
-
D.
grantType
Indicates the specific authorization or credential flow used to obtain access or permissions in a grant-based process.
-
E.
typeOfGrant
Indicates the specific category or kind of grant associated with an 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a544e3608190ac315c7aa9f88e7e |
completed | March 1, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ec8c748190b198492a0eea4445 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a54235548190b46218ea18f77341 |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:36 p.m.