Triple
T820610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alabama |
E17742
|
entity |
| Predicate | containsCounty |
P5971
|
FINISHED |
| Object |
Dale County
Dale County is a county in southeastern Alabama known for its association with Fort Novosel (formerly Fort Rucker) and its role in the Wiregrass region.
|
E187060
|
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: Dale County | Statement: [Alabama, containsCounty, Dale County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dale County Context triple: [Alabama, containsCounty, Dale County]
-
A.
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.
-
B.
Chilton County
Chilton County is a central Alabama county best known for its extensive peach orchards and agricultural production.
-
C.
Logan County
Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
-
D.
Dooly County
Dooly County is a rural county in central Georgia known for its agricultural economy and small-town communities.
-
E.
Pulaski County
Pulaski County is a rural county in central Georgia known for its agricultural landscape and the city of Hawkinsville as its county seat.
- 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: Dale County Triple: [Alabama, containsCounty, Dale County]
Generated description
Dale County is a county in southeastern Alabama known for its association with Fort Novosel (formerly Fort Rucker) and its role in the Wiregrass region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dale County Target entity description: Dale County is a county in southeastern Alabama known for its association with Fort Novosel (formerly Fort Rucker) and its role in the Wiregrass region.
-
A.
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.
-
B.
Chilton County
Chilton County is a central Alabama county best known for its extensive peach orchards and agricultural production.
-
C.
Logan County
Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
-
D.
Dooly County
Dooly County is a rural county in central Georgia known for its agricultural economy and small-town communities.
-
E.
Pulaski County
Pulaski County is a rural county in central Georgia known for its agricultural landscape and the city of Hawkinsville as its county seat.
- 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_69ad606f1c008190adca6fa6f0d6cd66 |
completed | March 8, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_69ad61ff65b881909009c230780a146e |
completed | March 8, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad62ec3a80819085fef1c378b9abdc |
completed | March 8, 2026, 11:52 a.m. |
Created at: March 1, 2026, 7:38 p.m.