Triple
T2719505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee County, Alabama |
E60047
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Kinston, Alabama
Kinston, Alabama is a small rural town in southeastern Alabama known for its close-knit community and agricultural surroundings.
|
E362564
|
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: Kinston, Alabama | Statement: [Coffee County, Alabama, hasTown, Kinston, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinston, Alabama Context triple: [Coffee County, Alabama, hasTown, Kinston, Alabama]
-
A.
Kingston, Alabama
Kingston, Alabama is an unincorporated rural community located in Shelby County in the central part of the state.
-
B.
Stanton, Alabama
Stanton, Alabama is a small unincorporated rural community located in Chilton County in the central part of the state.
-
C.
Tarrant, Alabama
Tarrant, Alabama is a small industrial city in Jefferson County, near Birmingham, known historically for its steel and manufacturing operations.
-
D.
Roanoke, Alabama
Roanoke, Alabama is a small city in eastern Alabama known for its rural character and role as a local commercial and community hub.
-
E.
Wilton, Alabama
Wilton, Alabama is a small town located in Shelby County in the central part of the state.
- 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: Kinston, Alabama Triple: [Coffee County, Alabama, hasTown, Kinston, Alabama]
Generated description
Kinston, Alabama is a small rural town in southeastern Alabama known for its close-knit community and agricultural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kinston, Alabama Target entity description: Kinston, Alabama is a small rural town in southeastern Alabama known for its close-knit community and agricultural surroundings.
-
A.
Kingston, Alabama
Kingston, Alabama is an unincorporated rural community located in Shelby County in the central part of the state.
-
B.
Stanton, Alabama
Stanton, Alabama is a small unincorporated rural community located in Chilton County in the central part of the state.
-
C.
Tarrant, Alabama
Tarrant, Alabama is a small industrial city in Jefferson County, near Birmingham, known historically for its steel and manufacturing operations.
-
D.
Roanoke, Alabama
Roanoke, Alabama is a small city in eastern Alabama known for its rural character and role as a local commercial and community hub.
-
E.
Wilton, Alabama
Wilton, Alabama is a small town located in Shelby County in the central part of the state.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaaee104819085966bc54d5da9c0 |
completed | March 7, 2026, 7:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37383fbf881909361d448de3c266b |
completed | March 13, 2026, 2:16 a.m. |
| NEDg | Description generation | batch_69b3746f1de4819091c5bcbf8a988ef1 |
completed | March 13, 2026, 2:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b374f5999c8190ae48570a412dc6dc |
completed | March 13, 2026, 2:22 a.m. |
Created at: March 6, 2026, 9:55 p.m.