Triple
T2150764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Court of Appeal |
E47173
|
entity |
| Predicate | canSitIn |
P36258
|
FINISHED |
| Object | other Canadian cities |
—
|
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: other Canadian cities | Statement: [Federal Court of Appeal, canSitIn, other Canadian cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canSitIn Context triple: [Federal Court of Appeal, canSitIn, other Canadian cities]
-
A.
maySitWith
Indicates that one entity is permitted or allowed to sit together with another entity.
-
B.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
canChair
Indicates that an entity has the authority or capability to preside over, lead, or chair a meeting, committee, or similar group.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
isSafeSeatFor
Indicates that one entity is a suitable and secure seating option for another entity, posing no unacceptable risk or harm.
- F. None of above. chosen
Provenance (4 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe4747a0819080e2234f3ea8995f |
completed | March 7, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbe4252688190944491a450383450 |
completed | March 7, 2026, 5:57 a.m. |
Created at: March 4, 2026, 7:44 p.m.