Triple
T6949521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Ontario Museum Act |
E160883
|
entity |
| Predicate | legalStatusOfSubject |
P2250
|
FINISHED |
| Object | public institution |
—
|
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: public institution | Statement: [Royal Ontario Museum Act, legalStatusOfSubject, public institution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusOfSubject Context triple: [Royal Ontario Museum Act, legalStatusOfSubject, public institution]
-
A.
hasLegalStatus
chosen
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
B.
usedLegalStatus
Indicates that one entity applies or relies on the legal status or classification of another entity in a given context.
-
C.
legalStatusClarifiedBy
Indicates that the legal status of something is defined, explained, or resolved by a specific document, decision, or authoritative act.
-
D.
legalStatusVariesBy
Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
-
E.
legalStatusInHomeland
Indicates the legal status or classification an entity holds within its country or place of origin.
- 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_69c68850419081909fb426b8f5a304c7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacca12481908942ba793a104cc3 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:29 p.m.