Triple
T22873924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Wizard’s Guide to Defensive Baking |
E567270
|
entity |
| Predicate | magicSpecialization |
P90354
|
FINISHED |
| Object | bread and baked goods |
—
|
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: bread and baked goods | Statement: [A Wizard’s Guide to Defensive Baking, magicSpecialization, bread and baked goods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: magicSpecialization Context triple: [A Wizard’s Guide to Defensive Baking, magicSpecialization, bread and baked goods]
-
A.
exportSpecialization
Indicates a relationship where one entity specializes in exporting particular goods, services, or resources to another entity or market.
-
B.
spellSpecialty
chosen
Indicates that an entity’s area of expertise or focus is a particular type or category of spell.
-
C.
materialSpecialization
Indicates a relationship where one material is a specialized, more specific, or refined form of another more general material.
-
D.
laterSpecialization
Indicates that one entity becomes a more specialized or refined version of another entity at a later point in time.
-
E.
magicField
Indicates the presence or influence of a magical force or energy affecting an entity or area.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f56d6448190ada4aef08eac2bed |
completed | April 29, 2026, 3:47 a.m. |
| PD | Predicate disambiguation | batch_69eed2d8c0608190afef4c4e530c0e2c |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:39 p.m.