Triple
T1169708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korstian Division |
E24885
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Duke Forest |
E3809
|
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: Duke Forest | Statement: [Korstian Division, locatedIn, Duke Forest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Duke Forest Context triple: [Korstian Division, locatedIn, Duke Forest]
-
A.
Duke Forest
chosen
Duke Forest is a large research, teaching, and recreational forest owned and managed by Duke University in the Durham, North Carolina area.
-
B.
McDonald Forest
McDonald Forest is a research and teaching forest near Corvallis, Oregon, managed by Oregon State University for studies in forestry, ecology, and natural resource management.
-
C.
Sarah Doublet Forest
Sarah Doublet Forest is a protected conservation area in Littleton, Massachusetts, known for its wooded trails, wildlife habitat, and opportunities for passive outdoor recreation.
-
D.
Talladega National Forest
Talladega National Forest is a federally protected forest in eastern Alabama known for its rugged Appalachian terrain, diverse wildlife, and extensive hiking and recreation opportunities.
-
E.
Dunn Forest
Dunn Forest is a component of Oregon State University's McDonald-Dunn Research Forest, used primarily for forestry research, education, and sustainable land management.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce821b481908bc278a3fa7973f4 |
completed | March 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f17aa608190920b7df62b8dd903 |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:45 p.m.