Triple
T820633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alabama |
E17742
|
entity |
| Predicate | containsCounty |
P5971
|
FINISHED |
| Object |
Hale County
Hale County is a rural county in west-central Alabama known for its agricultural landscape, small towns, and role in the Black Belt region.
|
E166077
|
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: Hale County | Statement: [Alabama, containsCounty, Hale County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hale County Context triple: [Alabama, containsCounty, Hale County]
-
A.
Crenshaw County
Crenshaw County is a rural county in south-central Alabama known for its agricultural landscape and small-town communities.
-
B.
Dooly County
Dooly County is a rural county in central Georgia known for its agricultural economy and small-town communities.
-
C.
LaRue County
LaRue County is a rural county in central Kentucky best known as the birthplace region of Abraham Lincoln, with Hodgenville as its county seat.
-
D.
Storey County
Storey County is a small, historic county in northern Nevada best known for the Comstock Lode mining district and the preserved 19th-century town of Virginia City.
-
E.
Logan County
Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
- 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: Hale County Triple: [Alabama, containsCounty, Hale County]
Generated description
Hale County is a rural county in west-central Alabama known for its agricultural landscape, small towns, and role in the Black Belt region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hale County Target entity description: Hale County is a rural county in west-central Alabama known for its agricultural landscape, small towns, and role in the Black Belt region.
-
A.
Crenshaw County
Crenshaw County is a rural county in south-central Alabama known for its agricultural landscape and small-town communities.
-
B.
Dooly County
Dooly County is a rural county in central Georgia known for its agricultural economy and small-town communities.
-
C.
LaRue County
LaRue County is a rural county in central Kentucky best known as the birthplace region of Abraham Lincoln, with Hodgenville as its county seat.
-
D.
Storey County
Storey County is a small, historic county in northern Nevada best known for the Comstock Lode mining district and the preserved 19th-century town of Virginia City.
-
E.
Logan County
Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab6698d881908d8c5d91259f97ec |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0895e1b48190921b5ba783823f3c |
completed | March 8, 2026, 5:26 a.m. |
| NEDg | Description generation | batch_69ad09bb040c8190bf014a9ff2249169 |
completed | March 8, 2026, 5:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad0a9956f8819081fd866c6f1ae5c7 |
completed | March 8, 2026, 5:35 a.m. |
Created at: March 1, 2026, 7:38 p.m.