Triple
T1533919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fulton Chain of Lakes |
E32506
|
entity |
| Predicate | hasScenicFeature |
P22129
|
FINISHED |
| Object | forested shorelines |
—
|
LITERAL 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: forested shorelines | Statement: [Fulton Chain of Lakes, hasScenicFeature, forested shorelines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScenicFeature Context triple: [Fulton Chain of Lakes, hasScenicFeature, forested shorelines]
-
A.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
B.
hasScenicDrive
Indicates that one entity offers or features a visually appealing or picturesque driving route associated with it.
-
C.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
D.
hasLandscapeFeatures
chosen
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
E.
hasScenicByway
Indicates that one place, route, or area is connected to or includes a designated scenic byway.
- F. None of above.
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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.