Triple
T24786051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Police magic unit |
E620118
|
entity |
| Predicate | alsoKnownAsInFandom |
P39
|
FINISHED |
| Object | magic unit of the Met |
—
|
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: magic unit of the Met | Statement: [Metropolitan Police magic unit, alsoKnownAsInFandom, magic unit of the Met]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoKnownAsInFandom Context triple: [Metropolitan Police magic unit, alsoKnownAsInFandom, magic unit of the Met]
-
A.
alsoKnownAs
chosen
Indicates that one entity is an alternative name, alias, or designation for another entity.
-
B.
fandomNickname
Indicates that one entity is the nickname used by fans to refer to another entity (such as a person, group, or work).
-
C.
followersKnownAs
Indicates that the followers of an entity are referred to by a particular name or label.
-
D.
fandomTerm
Indicates that one entity is a term, label, or piece of vocabulary specifically used within the fandom associated with another entity.
-
E.
hasFictionalAlias
Indicates that an entity is known by an alternative name or identity within a fictional context.
- 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_69e2fabdbe8c8190adbb9434b8636cad |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:45 a.m.