Triple
T32553620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jude Law as Albus Dumbledore |
E832036
|
entity |
| Predicate | wizardingStatus |
P62729
|
FINISHED |
| Object | half-blood wizard |
—
|
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: half-blood wizard | Statement: [Jude Law as Albus Dumbledore, wizardingStatus, half-blood wizard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wizardingStatus Context triple: [Jude Law as Albus Dumbledore, wizardingStatus, half-blood wizard]
-
A.
roleInHarryPotter
Indicates that one entity has a specific role or character part within the Harry Potter series in relation to the other entity.
-
B.
knowsAboutMagic
Indicates that one entity possesses knowledge or awareness of magic in relation to another entity or context.
-
C.
ministryOfMagicClassification
Indicates the official category or status assigned to something by the Ministry of Magic according to its classification system.
-
D.
magicalStatus
chosen
Indicates that an entity possesses, is affected by, or is characterized in terms of a particular magical condition or property.
-
E.
yearAtHogwarts
Indicates the specific academic year or level a person is in during their time at Hogwarts.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c5c87f2481908ebd32c6dd30ec89 |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:02 a.m.