Triple
T17610955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian territories |
E428962
|
entity |
| Predicate | haveDistinctLegalStatusFrom |
P21910
|
FINISHED |
| Object | Canadian provinces |
—
|
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: Canadian provinces | Statement: [Canadian territories, haveDistinctLegalStatusFrom, Canadian provinces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveDistinctLegalStatusFrom Context triple: [Canadian territories, haveDistinctLegalStatusFrom, Canadian provinces]
-
A.
hasSpecialLegalStatus
chosen
Indicates that an entity possesses a distinct, formally recognized legal standing or set of rights and obligations that differs from the standard legal status of comparable entities.
-
B.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
C.
hasNoLegalStatus
Indicates that the referenced entity lacks any formally recognized legal standing, rights, or status under the applicable legal system.
-
D.
usedLegalStatus
Indicates that one entity applies or relies on the legal status or classification of another entity in a given context.
-
E.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2d294881908380b2ab0b4d2503 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.