Triple
T7684625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iowa House of Representatives districts |
E174083
|
entity |
| Predicate | numberOfMembersPerDistrict |
P60915
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Iowa House of Representatives districts, numberOfMembersPerDistrict, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMembersPerDistrict Context triple: [Iowa House of Representatives districts, numberOfMembersPerDistrict, 1]
-
A.
numberOfDistrictMembers
chosen
Indicates the relationship that specifies how many members are associated with a given district.
-
B.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
C.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
D.
hasDistrictMembers
Indicates that a district includes or is composed of the specified members.
-
E.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7048b0b448190889bd40e0a38e51a |
completed | March 27, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69c701618d3481908be84b76f36ac5a1 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4:02 p.m.