Triple
T9908241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marshall County, Alabama |
E185071
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Douglas, Alabama
Douglas, Alabama is a small rural town in northeastern Alabama known for its close-knit community and agricultural surroundings.
|
E845410
|
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: Douglas, Alabama | Statement: [Marshall County, Alabama, containsSettlement, Douglas, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Douglas, Alabama Context triple: [Marshall County, Alabama, containsSettlement, Douglas, Alabama]
-
A.
Courtland, Alabama
Courtland, Alabama is a small historic town in northern Alabama known for its 19th-century architecture and role in the region’s early transportation and cotton economy.
-
B.
Brent, Alabama
Brent, Alabama is a small city in central Alabama known for its rural character and location within Bibb County.
-
C.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
-
D.
Morris, Alabama
Morris, Alabama is a small town in central Alabama that forms part of the Birmingham metropolitan area.
-
E.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
- 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: Douglas, Alabama Triple: [Marshall County, Alabama, containsSettlement, Douglas, Alabama]
Generated description
Douglas, Alabama is a small rural town in northeastern Alabama known for its close-knit community and agricultural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Douglas, Alabama Target entity description: Douglas, Alabama is a small rural town in northeastern Alabama known for its close-knit community and agricultural surroundings.
-
A.
Courtland, Alabama
Courtland, Alabama is a small historic town in northern Alabama known for its 19th-century architecture and role in the region’s early transportation and cotton economy.
-
B.
Brent, Alabama
Brent, Alabama is a small city in central Alabama known for its rural character and location within Bibb County.
-
C.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
-
D.
Morris, Alabama
Morris, Alabama is a small town in central Alabama that forms part of the Birmingham metropolitan area.
-
E.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50feb008190aa9c084f590c0ebd |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3000b21088190aa3ebb2ccbce9a6e |
completed | April 6, 2026, 12:36 a.m. |
| NEDg | Description generation | batch_69d301dd614481909b357f319ba5e876 |
completed | April 6, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d302978e808190a9f5371a2bf4abce |
completed | April 6, 2026, 12:47 a.m. |
Created at: March 30, 2026, 8:41 p.m.