Triple
T16078336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitchell County |
E390032
|
entity |
| Predicate | countySeat |
P383
|
FINISHED |
| Object |
Colorado City, Texas
Colorado City, Texas is a small West Texas community known historically for ranching, oil, and its role as a regional trade center.
|
E1195722
|
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: Colorado City, Texas | Statement: [Mitchell County, countySeat, Colorado City, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colorado City, Texas Context triple: [Mitchell County, countySeat, Colorado City, Texas]
-
A.
Coolidge, Texas
Coolidge, Texas is a small rural town in Limestone County known for its agricultural surroundings and location in central Texas.
-
B.
Crosbyton
Crosbyton is a small rural city in West Texas that serves as the administrative and commercial hub of Crosby County.
-
C.
Colfax, Texas
Colfax, Texas is a small unincorporated rural community located in Van Zandt County in East Texas.
-
D.
Cottonwood, Texas
Cottonwood, Texas is a small rural community located within Kaufman County in the state of Texas.
-
E.
Canyon, Texas
Canyon, Texas is a small city in the Texas Panhandle known as the home of West Texas A&M University and a gateway to nearby Palo Duro Canyon State Park.
- 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: Colorado City, Texas Triple: [Mitchell County, countySeat, Colorado City, Texas]
Generated description
Colorado City, Texas is a small West Texas community known historically for ranching, oil, and its role as a regional trade center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Colorado City, Texas Target entity description: Colorado City, Texas is a small West Texas community known historically for ranching, oil, and its role as a regional trade center.
-
A.
Coolidge, Texas
Coolidge, Texas is a small rural town in Limestone County known for its agricultural surroundings and location in central Texas.
-
B.
Crosbyton
Crosbyton is a small rural city in West Texas that serves as the administrative and commercial hub of Crosby County.
-
C.
Colfax, Texas
Colfax, Texas is a small unincorporated rural community located in Van Zandt County in East Texas.
-
D.
Cottonwood, Texas
Cottonwood, Texas is a small rural community located within Kaufman County in the state of Texas.
-
E.
Canyon, Texas
Canyon, Texas is a small city in the Texas Panhandle known as the home of West Texas A&M University and a gateway to nearby Palo Duro Canyon State Park.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183c401a881908fcb0b753d2dfc8a |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff29bc7408190be09bec1619b599c |
completed | May 10, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_69fff39371648190b3f694df00ff4f3e |
completed | May 10, 2026, 2:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff47a52cc8190b0ad7c37ea444159 |
completed | May 10, 2026, 2:59 a.m. |
Created at: April 10, 2026, 4:57 a.m.