Triple
T3053064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Courtney |
E60414
|
entity |
| Predicate | hostNationLanguage |
P13499
|
FINISHED |
| Object | Japanese |
—
|
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: Japanese | Statement: [Camp Courtney, hostNationLanguage, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostNationLanguage Context triple: [Camp Courtney, hostNationLanguage, Japanese]
-
A.
hostNationCapital
Indicates that a city serves as the capital of a particular host nation.
-
B.
hostNationRole
Indicates the role or capacity in which a nation serves as the host in a particular event, activity, or context.
-
C.
hostNationality
Indicates the national affiliation or citizenship of the host in a given hosting relationship or context.
-
D.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
E.
standardLanguageOf
chosen
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf3c52c8190bbe8e5cb98c21715 |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.