Triple
T16840779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fighting Dead Tree |
E409402
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Vermont |
E9978
|
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: Vermont | Statement: [Fighting Dead Tree, associatedWith, Vermont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vermont Context triple: [Fighting Dead Tree, associatedWith, Vermont]
-
A.
Vermont
Vermont is a small rural town located in Dane County, Wisconsin, known for its scenic landscapes and agricultural character.
-
B.
Vermont
chosen
Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
-
C.
Washington, Vermont
Washington, Vermont is a small rural town in central Vermont known for its scenic landscapes and traditional New England character.
-
D.
Georgia, Vermont
Georgia, Vermont is a small rural town in northwestern Vermont known for its agricultural landscape and proximity to Lake Champlain.
-
E.
New Hampshire
New Hampshire is a small New England state in the northeastern United States known for its mountainous landscapes, early presidential primary, and “Live Free or Die” motto.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b3508ecc81909c0af299e07f4b31 |
completed | April 18, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c79cdf9c8190aa20d536ca17ab81 |
completed | May 10, 2026, 5:59 p.m. |
Created at: April 10, 2026, 5:24 a.m.