Triple
T32613946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USCSS |
E833733
|
entity |
| Predicate | fictionalCountryOfRegistry |
P146637
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [USCSS, fictionalCountryOfRegistry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCountryOfRegistry Context triple: [USCSS, fictionalCountryOfRegistry, United States]
-
A.
countryOfRegistryInFiction
chosen
Indicates the fictional country in which an entity (such as a vehicle, vessel, or organization) is officially registered or flagged within a fictional context.
-
B.
countryOfRegistry
Indicates the country in which an entity (such as a ship, aircraft, or company) is officially registered.
-
C.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
D.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
E.
countryOfOriginFictional
Indicates that a fictional work, character, or element originates from or is associated with a particular country within its narrative or setting.
- 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
Created at: May 1, 2026, 1:06 a.m.