Triple
T8525847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hodgeman County, Kansas |
E201814
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Jetmore, Kansas |
E754215
|
NE 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: Jetmore, Kansas | Statement: [Hodgeman County, Kansas, largestCity, Jetmore, Kansas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jetmore, Kansas Context triple: [Hodgeman County, Kansas, largestCity, Jetmore, Kansas]
-
A.
Jetmore, Kansas
chosen
Jetmore, Kansas is a small rural city in western Kansas that serves as the administrative and commercial hub of Hodgeman County.
-
B.
Holcomb, Kansas
Holcomb, Kansas is a small rural village in western Kansas best known as the real-life setting of Truman Capote’s true-crime book "In Cold Blood."
-
C.
Merriam, Kansas
Merriam, Kansas is a small suburban city in Johnson County that forms part of the greater Kansas City metropolitan area.
-
D.
WaKeeney, Kansas
WaKeeney, Kansas is a small city in northwestern Kansas known as a regional service center along Interstate 70 and for its historic downtown and annual Christmas light displays.
-
E.
Emmett, Kansas
Emmett, Kansas is a small rural community in northeastern Kansas that functions as part of the broader Manhattan regional area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6463fe48190b6d3482212356be1 |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf5139150081909a020db7ca4bccc3 |
completed | April 3, 2026, 5:33 a.m. |
Created at: March 30, 2026, 6:16 p.m.