Triple
T1425107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas |
E30311
|
entity |
| Predicate | admittedToUnionAsStateNumber |
P28957
|
FINISHED |
| Object | 34 |
—
|
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: 34 | Statement: [Kansas, admittedToUnionAsStateNumber, 34]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: admittedToUnionAsStateNumber Context triple: [Kansas, admittedToUnionAsStateNumber, 34]
-
A.
admittedToUnionOn
Indicates that an entity (typically a state or region) was formally accepted and incorporated into a union or federation on a specific date.
-
B.
admittedToUnionFrom
Indicates that an entity (such as a state or region) was admitted into a union or larger political entity from a specified prior jurisdiction or status.
-
C.
admittedToUnionAs
Indicates that an entity (typically a state or region) was formally accepted and incorporated into a political union or federation in a specified capacity or status.
-
D.
statehoodYear
Indicates the year in which an entity officially became a recognized state or attained statehood status.
-
E.
admittedAsCountyWithStatehood
Indicates that an entity became a county at the same time its encompassing state was granted statehood.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8 p.m.