Triple
T3212544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Florida |
E67312
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object |
Taylor County
Taylor County is a rural county in Florida known for its Gulf Coast shoreline, forests, and small-town communities centered around the city of Perry.
|
E425429
|
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: Taylor County | Statement: [North Florida, includes, Taylor County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taylor County Context triple: [North Florida, includes, Taylor County]
-
A.
Taylor County
Taylor County is a rural county in southwestern Iowa known for its agricultural landscape and small communities.
-
B.
Taylor County
Taylor County is a rural county in west-central Georgia known for its small communities, agricultural landscape, and location along key state highways.
-
C.
Evans County
Evans County is a rural county in southeastern Georgia known for its agricultural landscape and small-town communities.
-
D.
Jones County
Jones County is a county in central Georgia, United States, known for its rural character and proximity to the city of Macon.
-
E.
Jones County
Jones County is a county in southeastern Mississippi known for its seat in Laurel and its historical role in the state's timber and agricultural industries.
- 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: Taylor County Triple: [North Florida, includes, Taylor County]
Generated description
Taylor County is a rural county in Florida known for its Gulf Coast shoreline, forests, and small-town communities centered around the city of Perry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taylor County Target entity description: Taylor County is a rural county in Florida known for its Gulf Coast shoreline, forests, and small-town communities centered around the city of Perry.
-
A.
Taylor County
Taylor County is a rural county in west-central Georgia known for its small communities, agricultural landscape, and location along key state highways.
-
B.
Taylor County
Taylor County is a rural county in southwestern Iowa known for its agricultural landscape and small communities.
-
C.
Evans County
Evans County is a rural county in southeastern Georgia known for its agricultural landscape and small-town communities.
-
D.
Jones County
Jones County is a county in central Georgia, United States, known for its rural character and proximity to the city of Macon.
-
E.
Jones County
Jones County is a county in southeastern Mississippi known for its seat in Laurel and its historical role in the state's timber and agricultural industries.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaabba8e481909118d9f888ddcd63 |
completed | March 8, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b73c409081909c583019d7ec1d4a |
completed | March 14, 2026, 7:30 p.m. |
| NEDg | Description generation | batch_69b5b7e7f48881908ebb773499aebd5e |
completed | March 14, 2026, 7:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5b881c80081909af084ff4b43b01e |
completed | March 14, 2026, 7:35 p.m. |
Created at: March 8, 2026, 3:07 p.m.