Triple
T15482106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moore County |
E376943
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Dumas, Texas |
—
|
NE NERFINISHED |
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: Dumas, Texas | Statement: [Moore County, hasCity, Dumas, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dumas, Texas Context triple: [Moore County, hasCity, Dumas, Texas]
-
A.
Dumas, Texas
chosen
Dumas, Texas is a small city in the Texas Panhandle known as a regional hub for agriculture and energy industries.
-
B.
Douglass, Texas
Douglass, Texas is a small unincorporated rural community in East Texas known for its close-knit population and agricultural surroundings.
-
C.
Vidor, Texas
Vidor, Texas is a small city in southeastern Texas known as a bedroom community of nearby Beaumont and part of the Beaumont–Port Arthur metropolitan area.
-
D.
DeSoto, Texas
DeSoto, Texas is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential communities and proximity to Dallas.
-
E.
Dorchester, Texas
Dorchester, Texas is a small rural community located in Grayson County in north-central Texas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8cb4388190a3b4c92c3bb4ad4f |
completed | April 16, 2026, 1:46 a.m. |
Created at: April 10, 2026, 3:38 a.m.