Triple
T11810723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emerald Mound |
E280864
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Adams County |
E570040
|
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: Adams County | Statement: [Emerald Mound, county, Adams County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adams County Context triple: [Emerald Mound, county, Adams County]
-
A.
Adams County
Adams County is a largely rural county in eastern Washington State known for its agricultural production, particularly wheat and potatoes.
-
B.
Adams County
Adams County is a rural county in central Wisconsin known for its forests, lakes, and outdoor recreation.
-
C.
Adams County
chosen
Adams County is a county in south-central Pennsylvania known for encompassing the historic town of Gettysburg and the Gettysburg National Military Park.
-
D.
Adams County
Adams County is a rural county in the southwestern part of the U.S. state of Iowa, known for its agricultural landscape and small communities.
-
E.
Grant County
Grant County is a rural county in eastern West Virginia known for its mountainous terrain, outdoor recreation areas, and small communities.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5ca50a081908a198b336d8c2b98 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4715720e08190a3bc1b4fc888fe79 |
completed | May 1, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:42 p.m.