Triple
T12915305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lowndes County, Alabama, United States |
E308964
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Benton, Alabama
Benton, Alabama is a small rural town situated along the Alabama River in central Alabama.
|
E1041901
|
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: Benton, Alabama | Statement: [Lowndes County, Alabama, United States, contains, Benton, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benton, Alabama Context triple: [Lowndes County, Alabama, United States, contains, Benton, Alabama]
-
A.
Brent, Alabama
Brent, Alabama is a small city in central Alabama known for its rural character and location within Bibb County.
-
B.
Butler, Alabama
Butler, Alabama is a small town in western Alabama that serves as the administrative and commercial center of Choctaw County.
-
C.
Berry, Alabama
Berry, Alabama is a small rural town in western Alabama known for its tight-knit community and location within Fayette County.
-
D.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
-
E.
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.
- 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: Benton, Alabama Triple: [Lowndes County, Alabama, United States, contains, Benton, Alabama]
Generated description
Benton, Alabama is a small rural town situated along the Alabama River in central Alabama.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Benton, Alabama Target entity description: Benton, Alabama is a small rural town situated along the Alabama River in central Alabama.
-
A.
Brent, Alabama
Brent, Alabama is a small city in central Alabama known for its rural character and location within Bibb County.
-
B.
Butler, Alabama
Butler, Alabama is a small town in western Alabama that serves as the administrative and commercial center of Choctaw County.
-
C.
Berry, Alabama
Berry, Alabama is a small rural town in western Alabama known for its tight-knit community and location within Fayette County.
-
D.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
-
E.
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.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971a0d6508190bca9668e9e06abfe |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7460999c081908c8d84caf6c04985 |
completed | May 3, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_69f74ab0b064819095ed05984f5e3d99 |
completed | May 3, 2026, 1:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f74b39fd88819099d48598316d5a97 |
completed | May 3, 2026, 1:18 p.m. |
Created at: April 9, 2026, 5:41 p.m.