Triple
T23639767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Man in Havana |
E583851
|
entity |
| Predicate | fictionalAgency |
P152992
|
FINISHED |
| Object | British Secret Service |
—
|
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: British Secret Service | Statement: [Our Man in Havana, fictionalAgency, British Secret Service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalAgency Context triple: [Our Man in Havana, fictionalAgency, British Secret Service]
-
A.
fictionalService
Indicates that one entity provides or is associated with an imagined or non-real service in relation to another entity.
-
B.
fictionalManager
Indicates that one entity serves as the (possibly invented or non-real) manager of another entity.
-
C.
fictionalCorporation
Indicates that an entity is a corporation that exists only in fiction rather than in the real world.
-
D.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
-
E.
worksForFictionalOrganization
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
- F. None of above. chosen
Provenance (4 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b27fc22c8190abda7398b9fb928c |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f1233300bc8190ac1639bdca1d7d99 |
completed | April 28, 2026, 9:14 p.m. |
Created at: April 17, 2026, 6:48 p.m.