Triple
T27751548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gandaki Provincial Assembly |
E701224
|
entity |
| Predicate | hasNumberOfFPTPSeats |
P48443
|
FINISHED |
| Object | 36 |
—
|
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: 36 | Statement: [Gandaki Provincial Assembly, hasNumberOfFPTPSeats, 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfFPTPSeats Context triple: [Gandaki Provincial Assembly, hasNumberOfFPTPSeats, 36]
-
A.
numberOfFPTPSeats
chosen
Indicates the number of seats obtained or allocated through a first-past-the-post (FPTP) electoral system.
-
B.
numberOfElectorates
Indicates the total count of electoral districts or constituencies associated with a given entity.
-
C.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
-
D.
hasNumberOfMPs
Indicates the relationship that specifies how many members of parliament (MPs) are associated with a given entity.
-
E.
hasNumberOfMSPs
Indicates the relationship specifying how many managed service providers (MSPs) are associated with or involved in a given entity or context.
- 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_69ef6a5193808190816eb7d0020b2d87 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 27, 2026, 4:20 p.m.