Triple
T36036490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain David Aceveda |
E1042415
|
entity |
| Predicate | homeNetworkCountry |
P1083
|
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: [Captain David Aceveda, homeNetworkCountry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeNetworkCountry Context triple: [Captain David Aceveda, homeNetworkCountry, United States]
-
A.
homeCountryRegion
Indicates the country or broader geographic region that is considered the primary home or origin of an entity.
-
B.
nativeCountry
Indicates the country in which an entity (typically a person) was born or is originally from.
-
C.
countryOrRegionUsed
Indicates that something is used within, or applies to, a specific country or geographic region.
-
D.
administrativeRegionCountry
Indicates that an administrative region is located within or belongs to a specific country.
-
E.
associatedCountry
chosen
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
- 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_69f76e2d7e8c8190bac4e90734566799 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ad1af4dc81908e3e7042f6c792e6 |
completed | May 3, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.