Triple
T28211280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malta STV elections |
E711175
|
entity |
| Predicate | typicalDistrictMagnitude |
P202366
|
FINISHED |
| Object | 5 seats per district |
—
|
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: 5 seats per district | Statement: [Malta STV elections, typicalDistrictMagnitude, 5 seats per district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDistrictMagnitude Context triple: [Malta STV elections, typicalDistrictMagnitude, 5 seats per district]
-
A.
typicalPopulationPerDistrict
Indicates the usual or average number of people found in each administrative district.
-
B.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
C.
typicalDistricts
Indicates that certain districts are characteristic or representative examples of a larger region, category, or entity.
-
D.
districtSize
Indicates the total physical area or extent of a district.
-
E.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a00776c4ebc8190899005fda34234d5 |
completed | May 10, 2026, 12:17 p.m. |
| PD | Predicate disambiguation | batch_6a0076f8a4c4819093ed577e67aa38f9 |
completed | May 10, 2026, 12:15 p.m. |
| PDg | Predicate description generation | batch_6a00776b69908190a431a48cc5e7dba9 |
completed | May 10, 2026, 12:17 p.m. |
Created at: April 27, 2026, 10:39 p.m.