Triple
T9836552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oxford, Maryland, United States |
E239116
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Talbot County |
E709962
|
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: Talbot County | Statement: [Oxford, Maryland, United States, county, Talbot County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talbot County Context triple: [Oxford, Maryland, United States, county, Talbot County]
-
A.
Talbot County
Talbot County is a county in west-central Georgia, United States, known for its rural character and historic small towns such as Talbotton.
-
B.
Talbot County
chosen
Talbot County is a county on Maryland’s Eastern Shore known for its historic towns, waterfront communities, and maritime heritage.
-
C.
Calhoun County
Calhoun County is a county in southern Michigan, United States, known for encompassing the city of Battle Creek and its surrounding communities.
-
D.
Calhoun County
Calhoun County is a rural county in the Florida Panhandle known for its forests, rivers, and small agricultural communities.
-
E.
Calhoun County
Calhoun County is a rural county in southwestern Georgia known for its agricultural landscape and small-town communities, including the city of Edison.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb33b07688190b78a70cf535c3efc |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257601eec8190b7fa205cee61bb23 |
completed | April 5, 2026, 12:36 p.m. |
Created at: March 30, 2026, 8:33 p.m.