Triple
T441327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Nigeria |
E10119
|
entity |
| Predicate | hasNumberOfConstituencies |
P13200
|
FINISHED |
| Object | 109 |
—
|
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: 109 | Statement: [Senate of Nigeria, hasNumberOfConstituencies, 109]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfConstituencies Context triple: [Senate of Nigeria, hasNumberOfConstituencies, 109]
-
A.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
-
B.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
-
C.
electoralConstituencies
Indicates a relationship where a geographic or political area is divided into specific electoral constituencies used for representation or voting.
-
D.
numberOfConstituents
Indicates the total count of individual components or members that make up a larger whole or group.
-
E.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef2af84881909635ebbbb3465b1b |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddcf50c8190bfa0d1f8ee9f604a |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.