Triple
T2719508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee County, Alabama |
E60047
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Chancellor, Alabama
Chancellor, Alabama is a small unincorporated community located in Coffee County in the southeastern part of the state.
|
E293183
|
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: Chancellor, Alabama | Statement: [Coffee County, Alabama, hasTown, Chancellor, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chancellor, Alabama Context triple: [Coffee County, Alabama, hasTown, Chancellor, Alabama]
-
A.
Tarrant, Alabama
Tarrant, Alabama is a small industrial city in Jefferson County, near Birmingham, known historically for its steel and manufacturing operations.
-
B.
Thach, Alabama
Thach, Alabama is a small unincorporated community located in Walker County in the U.S. state of Alabama.
-
C.
Waugh, Alabama
Waugh, Alabama is an unincorporated community in Montgomery County known for its rural character and location along U.S. Route 80 east of Montgomery.
-
D.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
E.
Ragland, Alabama
Ragland, Alabama is a small town in central Alabama known for its rural character and location within the Birmingham–Hoover metropolitan area.
- 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: Chancellor, Alabama Triple: [Coffee County, Alabama, hasTown, Chancellor, Alabama]
Generated description
Chancellor, Alabama is a small unincorporated community located in Coffee County in the southeastern part of the state.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chancellor, Alabama Target entity description: Chancellor, Alabama is a small unincorporated community located in Coffee County in the southeastern part of the state.
-
A.
Tarrant, Alabama
Tarrant, Alabama is a small industrial city in Jefferson County, near Birmingham, known historically for its steel and manufacturing operations.
-
B.
Thach, Alabama
Thach, Alabama is a small unincorporated community located in Walker County in the U.S. state of Alabama.
-
C.
Waugh, Alabama
Waugh, Alabama is an unincorporated community in Montgomery County known for its rural character and location along U.S. Route 80 east of Montgomery.
-
D.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
E.
Ragland, Alabama
Ragland, Alabama is a small town in central Alabama known for its rural character and location within the Birmingham–Hoover metropolitan area.
- 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_69afb68ebd0081908bb360872d559e1f |
completed | March 10, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69afb75ea498819089c79e63052e9696 |
completed | March 10, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb83ba6dc8190931d691d3e354bd7 |
completed | March 10, 2026, 6:20 a.m. |
Created at: March 6, 2026, 9:55 p.m.