Triple
T7283033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adirondack Forty-Six High Peaks |
E163796
|
entity |
| Predicate | hasNotablePeak |
P10602
|
FINISHED |
| Object | Colden |
E446497
|
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: Colden | Statement: [Adirondack Forty-Six High Peaks, hasNotablePeak, Colden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colden Context triple: [Adirondack Forty-Six High Peaks, hasNotablePeak, Colden]
-
A.
Tompkins
Tompkins is a surname most notably associated with Daniel D. Tompkins, the fourth governor of New York and seventh vice president of the United States.
-
B.
Colden, New York
chosen
Colden, New York is a small rural town in Erie County, New York, known for its scenic countryside and proximity to the Buffalo metropolitan area.
-
C.
Cresson
Cresson is a French surname most notably borne by Édith Cresson, who served as France’s first female prime minister.
-
D.
Randolph
Randolph is a character from Truman Capote’s Southern Gothic novel "Other Voices, Other Rooms," notable for his eccentric, theatrical personality and complex, ambiguous sexuality.
-
E.
Randolph
Randolph is the middle name of Hall of Fame basketball player and coach Leonard Wilkens.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb4ec2088190a6713eaa221d49a6 |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db3ae6a08190820c7096cbfea521 |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:59 p.m.