Triple
T27352744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R. H. Saunders Generating Station |
E684405
|
entity |
| Predicate | isBinationalComplexComponent |
P24635
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [R. H. Saunders Generating Station, isBinationalComplexComponent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBinationalComplexComponent Context triple: [R. H. Saunders Generating Station, isBinationalComplexComponent, yes]
-
A.
isBinationalComponentOf
chosen
Indicates that an entity is a component or part of a larger structure, project, or system that is jointly established, managed, or recognized by two nations.
-
B.
isBinational
Indicates that an entity is associated with or recognized by two distinct nations, such as holding dual nationality or operating under the authority of two countries.
-
C.
hasMajorBinationalComponent
Indicates that something involves a significant component jointly undertaken, governed, or shared by two different nations.
-
D.
isBinationalUrbanArea
Indicates that an urban area spans across and functionally integrates cities or communities in two different nations.
-
E.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
- 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_69ef1480a76481908684256ddd5bfda3 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f62c1b91e881908798e4f00723efcb |
completed | May 2, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69f620e4b1c88190a17940251abc68fd |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 11:49 a.m.