Triple
T16226860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgan County, Alabama |
E393871
|
entity |
| Predicate | originalName |
P65
|
FINISHED |
| Object |
Cotaco County
Cotaco County was the original name of what is now Morgan County in northern Alabama, a region along the Tennessee River.
|
E1200827
|
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: Cotaco County | Statement: [Morgan County, Alabama, originalName, Cotaco County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cotaco County Context triple: [Morgan County, Alabama, originalName, Cotaco County]
-
A.
Weston County
Weston County is a rural county in northeastern Wyoming known for its ranching, coal mining, and forested landscapes near the Black Hills.
-
B.
Mills County
Mills County is a rural county in the southwestern part of the U.S. state of Iowa, known for its agricultural landscape and small communities.
-
C.
Runnels County
Runnels County is a rural county in west-central Texas known for its agricultural economy and small-town communities.
-
D.
Llano County
Llano County is a rural county in central Texas known for its scenic Hill Country landscapes, granite outcrops, and outdoor recreation around lakes and rivers.
-
E.
Tandora County
Tandora County is a cadastral land division in New South Wales, Australia, used primarily for property and land title purposes.
- 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: Cotaco County Triple: [Morgan County, Alabama, originalName, Cotaco County]
Generated description
Cotaco County was the original name of what is now Morgan County in northern Alabama, a region along the Tennessee River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cotaco County Target entity description: Cotaco County was the original name of what is now Morgan County in northern Alabama, a region along the Tennessee River.
-
A.
Weston County
Weston County is a rural county in northeastern Wyoming known for its ranching, coal mining, and forested landscapes near the Black Hills.
-
B.
Mills County
Mills County is a rural county in the southwestern part of the U.S. state of Iowa, known for its agricultural landscape and small communities.
-
C.
Runnels County
Runnels County is a rural county in west-central Texas known for its agricultural economy and small-town communities.
-
D.
Llano County
Llano County is a rural county in central Texas known for its scenic Hill Country landscapes, granite outcrops, and outdoor recreation around lakes and rivers.
-
E.
Tandora County
Tandora County is a cadastral land division in New South Wales, Australia, used primarily for property and land title purposes.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d26b02c819080b70ab7cc3bcc24 |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00079c4184819091d3355a5afaeced |
completed | May 10, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_6a0009f631e08190aae358edc9ffad6b |
completed | May 10, 2026, 4:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a000a6de0488190ac72fb9eee9ec531 |
completed | May 10, 2026, 4:32 a.m. |
Created at: April 10, 2026, 5:03 a.m.