Triple
T1052115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alaska House of Representatives |
E22721
|
entity |
| Predicate | numberOfLegislativeDistricts |
P1679
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Alaska House of Representatives, numberOfLegislativeDistricts, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLegislativeDistricts Context triple: [Alaska House of Representatives, numberOfLegislativeDistricts, 40]
-
A.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
B.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
-
C.
hasNumberOfSenatorialDivisions
Indicates the relationship that specifies how many senatorial divisions are associated with a given entity.
-
D.
congressionalDistrict
Indicates that one entity is a congressional district that politically represents or geographically contains the other entity.
-
E.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b5312081909796df58fa7c1e9d |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.