Triple
T3832898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellis USD 388 |
E91055
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Ellis County |
E364565
|
NE FINISHED |
How this triple was built (2 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: Ellis County | Statement: [Ellis USD 388, county, Ellis County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellis County Context triple: [Ellis USD 388, county, Ellis County]
-
A.
Ellis County
chosen
Ellis County is a rural county in northwestern Oklahoma known for its agricultural economy and small, sparsely populated communities.
-
B.
Randall County
Randall County is a county in the Texas Panhandle region, known for including part of the city of Amarillo and featuring a mix of urban and rural High Plains landscapes.
-
C.
Donley County
Donley County is a rural county in the Texas Panhandle known for its ranching heritage, small communities, and wide-open High Plains landscapes.
-
D.
Harding County
Harding County is a sparsely populated rural county in northeastern New Mexico known for its ranching landscape and wide-open high plains.
-
E.
Burnet County
Burnet County is a central Texas county known for its scenic lakes, rolling hills, and outdoor recreation in the Texas Hill Country.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb88b8a8819082d4bdbc5bc45366 |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdf9f26be48190bf21b252a922ca69 |
completed | March 21, 2026, 1:52 a.m. |
Created at: March 9, 2026, 3:17 p.m.