Triple
T35830550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nielas Aran |
E1035785
|
entity |
| Predicate | magicUserType |
P184163
|
FINISHED |
| Object | Mage |
—
|
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: Mage | Statement: [Nielas Aran, magicUserType, Mage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: magicUserType Context triple: [Nielas Aran, magicUserType, Mage]
-
A.
MACType
Indicates the type or category of a Medium Access Control (MAC) mechanism or protocol used in a communication system.
-
B.
associatedWithMagicUser
Indicates a relationship in which an entity has a connection or involvement with a magic user, such as collaboration, affiliation, or influence.
-
C.
supportsUserType
Indicates that one entity is compatible with, or provides functionality for, a specified type or category of user.
-
D.
primaryUserType
Indicates the main or dominant category of user associated with an entity or interaction.
-
E.
speciesOfPrimaryUser
Indicates the biological species to which the primary user of something (e.g., a device, service, or resource) belongs.
- 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:06 p.m.