Triple
T480197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Assembly of Nigeria |
E9150
|
entity |
| Predicate | chamberCount |
P1545
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [National Assembly of Nigeria, chamberCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chamberCount Context triple: [National Assembly of Nigeria, chamberCount, 2]
-
A.
numberOfChambers
chosen
Indicates the count of distinct chambers or compartments associated with an entity.
-
B.
chamber1
Indicates that an entity is a chamber or room, typically serving as an enclosed space within a larger structure.
-
C.
chamberType
Indicates the specific kind or category of chamber associated with an entity (e.g., room, compartment, or enclosed space type).
-
D.
chamber2
Indicates that one entity serves as a secondary or inner chamber, room, or compartment associated with another entity.
-
E.
chamberedFor
Indicates that a firearm is designed or configured to safely accept and fire a specific cartridge or ammunition type in its chamber.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f057c4ac819080cf43ffaa56c350 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf1d5848190a7da27e2fddc136f |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.