Triple
T4286311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willow Ufgood |
E97276
|
entity |
| Predicate | magicType |
P19914
|
FINISHED |
| Object | apprentice sorcerer |
—
|
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: apprentice sorcerer | Statement: [Willow Ufgood, magicType, apprentice sorcerer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: magicType Context triple: [Willow Ufgood, magicType, apprentice sorcerer]
-
A.
typeOfMagic
chosen
Indicates that one entity is a specific category, school, or kind of magic associated with another entity.
-
B.
usesMagic
Indicates that an entity performs actions or achieves effects by employing magical powers or supernatural abilities.
-
C.
usesMagicFor
Indicates that one entity employs or applies magic as a means to achieve, affect, or perform something involving another entity or context.
-
D.
modeType
Indicates the specific manner, method, or operational mode in which an action, process, or system is carried out or functions.
-
E.
involvesMagic
Indicates that the related action, event, or relationship includes the use or presence of magical powers, forces, or phenomena.
- F. None of above.
Provenance (3 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3505d23d88190a638f2cc2acee9ee |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.