Triple
T3796746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wamego USD 320 |
E91587
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object |
Wamego, Kansas
Wamego, Kansas is a small city in northeastern Kansas known for its agricultural roots, community-focused atmosphere, and attractions like its Oz-themed tourism sites.
|
E398596
|
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: Wamego, Kansas | Statement: [Wamego USD 320, servesCity, Wamego, Kansas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wamego, Kansas Context triple: [Wamego USD 320, servesCity, Wamego, Kansas]
-
A.
De Soto, Kansas
De Soto, Kansas is a small city in northeastern Kansas that forms part of the Kansas City metropolitan area.
-
B.
Weir, Kansas
Weir, Kansas is a small city located in southeastern Kansas within Cherokee County.
-
C.
Hepler, Kansas
Hepler, Kansas is a small rural town located in southeastern Kansas within Crawford County.
-
D.
Ellsworth, Kansas
Ellsworth, Kansas is a small central Kansas city historically known as a 19th-century cattle town and later as the site of institutions such as St. Joseph Military Academy.
-
E.
Walnut, Kansas
Walnut, Kansas is a small rural city located in Crawford County in southeastern Kansas, known for its agricultural surroundings and close-knit community.
- 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: Wamego, Kansas Triple: [Wamego USD 320, servesCity, Wamego, Kansas]
Generated description
Wamego, Kansas is a small city in northeastern Kansas known for its agricultural roots, community-focused atmosphere, and attractions like its Oz-themed tourism sites.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wamego, Kansas Target entity description: Wamego, Kansas is a small city in northeastern Kansas known for its agricultural roots, community-focused atmosphere, and attractions like its Oz-themed tourism sites.
-
A.
De Soto, Kansas
De Soto, Kansas is a small city in northeastern Kansas that forms part of the Kansas City metropolitan area.
-
B.
Weir, Kansas
Weir, Kansas is a small city located in southeastern Kansas within Cherokee County.
-
C.
Hepler, Kansas
Hepler, Kansas is a small rural town located in southeastern Kansas within Crawford County.
-
D.
Ellsworth, Kansas
Ellsworth, Kansas is a small central Kansas city historically known as a 19th-century cattle town and later as the site of institutions such as St. Joseph Military Academy.
-
E.
Walnut, Kansas
Walnut, Kansas is a small rural city located in Crawford County in southeastern Kansas, known for its agricultural surroundings and close-knit community.
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee7a0818481909460197929ebb8e4 |
completed | March 9, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5282f253c81908c18a30bb1025f99 |
completed | March 14, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69b528d33c2081908e5f74005679dfbe |
completed | March 14, 2026, 9:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5294c66588190ad7cc8e87b58ff52 |
completed | March 14, 2026, 9:24 a.m. |
Created at: March 9, 2026, 3:15 p.m.