Triple
T18733593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Houston County, Georgia |
E458101
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Elko, Georgia |
—
|
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: Elko, Georgia | Statement: [Houston County, Georgia, contains, Elko, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elko, Georgia Context triple: [Houston County, Georgia, contains, Elko, Georgia]
-
A.
Elko, Georgia
chosen
Elko, Georgia is a small unincorporated community and rural locality in central Georgia.
-
B.
Elberton, Georgia
Elberton, Georgia is a small city in northeastern Georgia known as the "Granite Capital of the World" for its extensive granite quarrying and monument industry.
-
C.
De Soto, Georgia
De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
-
D.
Lovett, Georgia
Lovett, Georgia is a small unincorporated rural community located in Laurens County in the central part of the state.
-
E.
Blakely, Georgia
Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d791ab88190b333503f9b1ad0c0 |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.