Triple
T28868335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Robert Borden High School |
E729064
|
entity |
| Predicate | hasNamesakeCountryOfCitizenship |
P35759
|
FINISHED |
| Object | Canada |
—
|
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: Canada | Statement: [Sir Robert Borden High School, hasNamesakeCountryOfCitizenship, Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamesakeCountryOfCitizenship Context triple: [Sir Robert Borden High School, hasNamesakeCountryOfCitizenship, Canada]
-
A.
hasEponymCitizenship
chosen
Indicates that an entity’s eponym (the person or figure it is named after) holds or held a particular citizenship or national affiliation.
-
B.
hasBiographicalSubjectCitizenship
Indicates that the biographical subject holds or has held citizenship in the specified country or political entity.
-
C.
creatorCountryOfCitizenship
Indicates the country in which the creator holds or held legal citizenship.
-
D.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
E.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
- 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_69f031a01cbc8190ba87270bb6fe4639 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 28, 2026, 6:49 a.m.