Triple
T18792914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Philippine Duchesne |
E459560
|
entity |
| Predicate | activityRegion |
P285
|
FINISHED |
| Object | Kansas, United States |
—
|
NE NERFINISHED |
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: Kansas, United States | Statement: [Saint Philippine Duchesne, activityRegion, Kansas, United States]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kansas, United States Context triple: [Saint Philippine Duchesne, activityRegion, Kansas, United States]
-
A.
Kansas
chosen
Kansas is a largely rural, landlocked U.S. state known for its extensive plains, agricultural production, and central location within the country.
-
B.
Kansas, Georgia
Kansas, Georgia is a small unincorporated rural community located in Carroll County in the western part of the state.
-
C.
Kansas, Alabama
Kansas, Alabama is a small unincorporated rural community located in Walker County in the U.S. state of Alabama.
-
D.
Lakin, Kansas
Lakin, Kansas is a small city in southwestern Kansas that serves as the administrative and economic center of Kearny County.
-
E.
Wichita, Kansas, United States
Wichita, Kansas, United States, is the largest city in Kansas and a major regional center for aviation manufacturing and industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e59787e5988190883ed575ab4b6dec |
completed | April 20, 2026, 3:03 a.m. |
Created at: April 10, 2026, 11:53 a.m.