Triple
T19345198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas congressional delegation |
E483857
|
entity |
| Predicate | typicalHouseSeatCount |
P135503
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Kansas congressional delegation, typicalHouseSeatCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalHouseSeatCount Context triple: [Kansas congressional delegation, typicalHouseSeatCount, 4]
-
A.
typicalHomeCapacity
Indicates the usual or standard number of occupants that a home is designed or expected to accommodate.
-
B.
numberOfBedrooms
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
C.
hasNumberOfHouses
Indicates the quantity of houses associated with a given entity.
-
D.
typicalHouse
Indicates that something is a standard or representative example of a house in terms of its usual features, structure, or characteristics.
-
E.
numberOfHouses
Indicates the quantity of houses associated with a given entity or context.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6185a56b4819089336564959b84df |
completed | April 20, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:34 p.m.