Triple
T5691436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeast Kansas |
E125435
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Chanute, Kansas
Chanute, Kansas is a small city in Neosho County known historically as a regional railroad and industrial hub in southeastern Kansas.
|
E572090
|
NE FINISHED |
How this triple was built (4 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: Chanute, Kansas | Statement: [Southeast Kansas, contains, Chanute, Kansas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chanute, Kansas Context triple: [Southeast Kansas, contains, Chanute, Kansas]
-
A.
Watson, Kansas
Watson, Kansas is a small unincorporated rural community located in Shawnee County in the U.S. state of Kansas.
-
B.
Tecumseh, Kansas
Tecumseh, Kansas is a small unincorporated community in northeastern Kansas, located just east of Topeka along the Kansas River.
-
C.
Schoenchen, Kansas
Schoenchen, Kansas is a small rural city in central Kansas known for its German-Russian heritage and close-knit community.
-
D.
Belvue, Kansas
Belvue, Kansas is a small rural city in Pottawatomie County that functions as part of the greater Manhattan, Kansas regional community.
-
E.
Chapman, Kansas
Chapman, Kansas is a small rural city in central Kansas known for its tight-knit community and agricultural surroundings.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chanute, Kansas Triple: [Southeast Kansas, contains, Chanute, Kansas]
Generated description
Chanute, Kansas is a small city in Neosho County known historically as a regional railroad and industrial hub in southeastern Kansas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chanute, Kansas Target entity description: Chanute, Kansas is a small city in Neosho County known historically as a regional railroad and industrial hub in southeastern Kansas.
-
A.
Watson, Kansas
Watson, Kansas is a small unincorporated rural community located in Shawnee County in the U.S. state of Kansas.
-
B.
Tecumseh, Kansas
Tecumseh, Kansas is a small unincorporated community in northeastern Kansas, located just east of Topeka along the Kansas River.
-
C.
Schoenchen, Kansas
Schoenchen, Kansas is a small rural city in central Kansas known for its German-Russian heritage and close-knit community.
-
D.
Belvue, Kansas
Belvue, Kansas is a small rural city in Pottawatomie County that functions as part of the greater Manhattan, Kansas regional community.
-
E.
Chapman, Kansas
Chapman, Kansas is a small rural city in central Kansas known for its tight-knit community and agricultural surroundings.
- F. None of above. chosen
Provenance (5 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e500ec8190bfda4f6a818aa5dc |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1352809748190bca3b862c72a70f4 |
completed | March 23, 2026, 12:42 p.m. |
| NEDg | Description generation | batch_69c13858ef8481909f7db81f5be53f30 |
completed | March 23, 2026, 12:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c138c34b3081909852329804f30cf2 |
completed | March 23, 2026, 12:57 p.m. |
Created at: March 22, 2026, 3:44 p.m.