Triple
T7268923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camel’s Hump |
E161049
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Duxbury, Vermont |
E214239
|
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: Duxbury, Vermont | Statement: [Camel’s Hump, hasNearbyTown, Duxbury, Vermont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Duxbury, Vermont Context triple: [Camel’s Hump, hasNearbyTown, Duxbury, Vermont]
-
A.
Duxbury, Vermont
chosen
Duxbury, Vermont is a small rural town in central Vermont known for its forested landscape and proximity to the Green Mountains.
-
B.
Roxbury, Vermont
Roxbury, Vermont is a small rural town in central Vermont known for its mountainous landscape, forests, and outdoor recreation opportunities.
-
C.
Waltham, Vermont
Waltham, Vermont is a small rural town located in Addison County in the western part of the state.
-
D.
Westford, Vermont
Westford, Vermont is a small rural town in northwestern Vermont known for its scenic landscapes and close-knit community within the Burlington metropolitan area.
-
E.
Brookline, Vermont
Brookline, Vermont is a small rural town in southeastern Vermont known for its scenic landscapes and quiet, close-knit community.
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eae8cc288190bc3ae3c7b38980d0 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eed8c5448190b83faee62f8122de |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 2:58 p.m.