Triple
T20427872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Magical Law Enforcement |
E501050
|
entity |
| Predicate | employs |
P7
|
FINISHED |
| Object | Auror |
—
|
NE NERFINISHED |
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: Auror | Statement: [Department of Magical Law Enforcement, employs, Auror]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Auror Context triple: [Department of Magical Law Enforcement, employs, Auror]
-
A.
Auror
chosen
An Auror is a highly trained dark-wizard catcher and elite law-enforcement officer in the Harry Potter universe, working for the Ministry of Magic to combat dark magic and its practitioners.
-
B.
Aurora
Aurora is a Norwegian singer-songwriter known for her ethereal vocals, atmospheric electropop sound, and introspective, nature-inspired lyrics.
-
C.
Aurora
Aurora is an autonomous vehicle technology company focused on developing self-driving systems for cars, trucks, and other vehicles.
-
D.
Aurora
Aurora is a protected entity or realm under the guardianship of the being known as Fauna.
-
E.
Aurora
Aurora is a major suburban city in the Denver metropolitan area of Colorado, known for its diverse population, extensive parks and open spaces, and role as a key economic and residential hub on the eastern side of the metro region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67baa91b881909dfd68ccca25063c |
completed | April 20, 2026, 7:16 p.m. |
Created at: April 16, 2026, 11:31 a.m.