Triple
T1157324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Council of Provinces |
E24411
|
entity |
| Predicate | hasNumberOfDelegatesPerProvince |
P10538
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [National Council of Provinces, hasNumberOfDelegatesPerProvince, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfDelegatesPerProvince Context triple: [National Council of Provinces, hasNumberOfDelegatesPerProvince, 10]
-
A.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
-
B.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
-
C.
numberOfProvinces
Indicates the total count of provinces associated with a given entity or within a specified region or country.
-
D.
numberOfDelegates
chosen
Indicates the quantity of delegates associated with or assigned to a particular entity or event.
-
E.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc92ae008190a587c12ecc9a502a |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.