Triple
T5668936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas County, Alabama |
E124924
|
entity |
| Predicate | hasUnincorporatedCommunity |
P6345
|
FINISHED |
| Object |
Tyler, Alabama
Tyler, Alabama is a small unincorporated rural community located in Dallas County in the central part of the state.
|
E562751
|
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: Tyler, Alabama | Statement: [Dallas County, Alabama, hasUnincorporatedCommunity, Tyler, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyler, Alabama Context triple: [Dallas County, Alabama, hasUnincorporatedCommunity, Tyler, Alabama]
-
A.
Taylor, Alabama
Taylor, Alabama is a small town located in southeastern Alabama that is part of the Dothan metropolitan area.
-
B.
Moody, Alabama
Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
-
C.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
D.
Grant, Alabama
Grant, Alabama is a small town in Marshall County known as the closest community to Cathedral Caverns State Park in the Appalachian region of northern Alabama.
-
E.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
- 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: Tyler, Alabama Triple: [Dallas County, Alabama, hasUnincorporatedCommunity, Tyler, Alabama]
Generated description
Tyler, Alabama is a small unincorporated rural community located in Dallas County in the central part of the state.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tyler, Alabama Target entity description: Tyler, Alabama is a small unincorporated rural community located in Dallas County in the central part of the state.
-
A.
Taylor, Alabama
Taylor, Alabama is a small town located in southeastern Alabama that is part of the Dothan metropolitan area.
-
B.
Moody, Alabama
Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
-
C.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
D.
Grant, Alabama
Grant, Alabama is a small town in Marshall County known as the closest community to Cathedral Caverns State Park in the Appalachian region of northern Alabama.
-
E.
Billingsley, Alabama
Billingsley, Alabama is a small rural town in central Alabama known for its close-knit community and agricultural surroundings.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0234891d48190bf662f38ef84d4f3 |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c107bf6994819089e1211ffe343094 |
completed | March 23, 2026, 9:28 a.m. |
| NEDg | Description generation | batch_69c1090a7bac8190b5b9e003659b4b34 |
completed | March 23, 2026, 9:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10d5102348190a9ec7421b1410a99 |
completed | March 23, 2026, 9:52 a.m. |
Created at: March 22, 2026, 3:43 p.m.