Triple
T802603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Canada |
E17160
|
entity |
| Predicate | hasMaximumNumberOfMembers |
P21198
|
FINISHED |
| Object | 105 |
—
|
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: 105 | Statement: [Senate of Canada, hasMaximumNumberOfMembers, 105]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumNumberOfMembers Context triple: [Senate of Canada, hasMaximumNumberOfMembers, 105]
-
A.
hasCurrentNumberOfMembers
Indicates the current count of members associated with a given entity.
-
B.
minimumNumberOfMembers
Indicates the smallest allowable or required number of members that must be present or involved in a given context or group.
-
C.
hasMembers
Indicates that a group, organization, or collection includes certain entities as its members.
-
D.
additionalMembersAllowed
Indicates that more members are permitted to be added beyond those already included or initially specified.
-
E.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ace495348190aec66f35ea90bc89 |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa70973c8190adbf08302d1103a9 |
completed | March 1, 2026, 9:06 p.m. |
| PDg | Predicate description generation | batch_69a4ace369b481908ad69de6de99f5e6 |
completed | March 1, 2026, 9:17 p.m. |
Created at: March 1, 2026, 7:38 p.m.