Triple
T28230797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Private Berlin |
E711723
|
entity |
| Predicate | fictionalDetectiveAgencyBranch |
P152992
|
FINISHED |
| Object | Private Berlin office |
—
|
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: Private Berlin office | Statement: [Private Berlin, fictionalDetectiveAgencyBranch, Private Berlin office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalDetectiveAgencyBranch Context triple: [Private Berlin, fictionalDetectiveAgencyBranch, Private Berlin office]
-
A.
fictionalDetective
Indicates that the subject is a detective character who exists only in fiction rather than in real life.
-
B.
fictionalAgency
chosen
Indicates a relationship in which an entity is associated with, created by, or operating under an organization that exists only within a fictional or imaginary context.
-
C.
hasFictionalPoliceDepartment
Indicates that an entity is associated with or features a police department that exists only within a fictional or imaginary context.
-
D.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
E.
rivalFictionalAgency
Indicates that one fictional agency stands in opposition or competition to another fictional agency.
- 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_69efb51ece308190b8c269a057e36652 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: April 27, 2026, 10:52 p.m.