Triple
T12835915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scurry County |
E306911
|
entity |
| Predicate | countySeat |
P383
|
FINISHED |
| Object |
Snyder, Texas
Snyder, Texas is a small West Texas city that serves as a regional hub for ranching, oil, and gas activity.
|
E1092646
|
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: Snyder, Texas | Statement: [Scurry County, countySeat, Snyder, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snyder, Texas Context triple: [Scurry County, countySeat, Snyder, Texas]
-
A.
Sanger, Texas
Sanger, Texas is a small city in Denton County known for its rural character and proximity to outdoor recreation at Ray Roberts Lake.
-
B.
Stinnett, Texas
Stinnett, Texas is a small city in the Texas Panhandle that serves as an administrative and service hub for the surrounding rural area.
-
C.
Sinton, Texas
Sinton, Texas is a small city in San Patricio County that serves as part of the Coastal Bend region near the Texas Gulf Coast.
-
D.
Sanderson, Texas
Sanderson, Texas is a small unincorporated community and county seat of Terrell County in West Texas, known as a remote desert town along major highways and railroad lines.
-
E.
Sachse, Texas
Sachse, Texas is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential communities and proximity to major North Texas employment and retail centers.
- 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: Snyder, Texas Triple: [Scurry County, countySeat, Snyder, Texas]
Generated description
Snyder, Texas is a small West Texas city that serves as a regional hub for ranching, oil, and gas activity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snyder, Texas Target entity description: Snyder, Texas is a small West Texas city that serves as a regional hub for ranching, oil, and gas activity.
-
A.
Sanger, Texas
Sanger, Texas is a small city in Denton County known for its rural character and proximity to outdoor recreation at Ray Roberts Lake.
-
B.
Stinnett, Texas
Stinnett, Texas is a small city in the Texas Panhandle that serves as an administrative and service hub for the surrounding rural area.
-
C.
Sinton, Texas
Sinton, Texas is a small city in San Patricio County that serves as part of the Coastal Bend region near the Texas Gulf Coast.
-
D.
Sanderson, Texas
Sanderson, Texas is a small unincorporated community and county seat of Terrell County in West Texas, known as a remote desert town along major highways and railroad lines.
-
E.
Sachse, Texas
Sachse, Texas is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential communities and proximity to major North Texas employment and retail centers.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff015f4819090070a01f3938acc |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd466577508190b1926c475b7c49dc |
completed | May 8, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69fd4768edc881909a0c586b6d9568a3 |
completed | May 8, 2026, 2:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd47eb7db08190a68f60b255073d8d |
completed | May 8, 2026, 2:18 a.m. |
Created at: April 9, 2026, 5:35 p.m.