Triple
T2300559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Panhandle |
E51719
|
entity |
| Predicate | hasCounty |
P285
|
FINISHED |
| Object |
Borden County
Borden County is a sparsely populated rural county in western Texas known for its ranching economy and wide-open plains.
|
E380048
|
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: Borden County | Statement: [Texas Panhandle, hasCounty, Borden County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borden County Context triple: [Texas Panhandle, hasCounty, Borden County]
-
A.
Burnet County
Burnet County is a central Texas county known for its scenic lakes, rolling hills, and outdoor recreation in the Texas Hill Country.
-
B.
Gray County
Gray County is a rural county in the Texas Panhandle best known for its oil industry and county seat, Pampa.
-
C.
Hastings County
Hastings County is a large, predominantly rural county in eastern Ontario, Canada, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Briscoe County
Briscoe County is a rural county in the Texas Panhandle known for its agricultural economy and proximity to the scenic Caprock Canyons region.
-
E.
Dallam County
Dallam County is a sparsely populated rural county in the far northwestern corner of the Texas Panhandle, known for its agricultural economy and wide-open High Plains landscape.
- 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: Borden County Triple: [Texas Panhandle, hasCounty, Borden County]
Generated description
Borden County is a sparsely populated rural county in western Texas known for its ranching economy and wide-open plains.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Borden County Target entity description: Borden County is a sparsely populated rural county in western Texas known for its ranching economy and wide-open plains.
-
A.
Burnet County
Burnet County is a central Texas county known for its scenic lakes, rolling hills, and outdoor recreation in the Texas Hill Country.
-
B.
Gray County
Gray County is a rural county in the Texas Panhandle best known for its oil industry and county seat, Pampa.
-
C.
Hastings County
Hastings County is a large, predominantly rural county in eastern Ontario, Canada, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Briscoe County
Briscoe County is a rural county in the Texas Panhandle known for its agricultural economy and proximity to the scenic Caprock Canyons region.
-
E.
Dallam County
Dallam County is a sparsely populated rural county in the far northwestern corner of the Texas Panhandle, known for its agricultural economy and wide-open High Plains landscape.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5edc1348190a4d84606b1310711 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c34fb7d881908d45f96f621d26ad |
completed | March 14, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69b4c713c3888190bfcdf5fe9b3969c2 |
completed | March 14, 2026, 2:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c7b31e648190b9b8e1f761163035 |
completed | March 14, 2026, 2:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.