Triple
T7914073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pell City, Alabama |
E183772
|
entity |
| Predicate | hasLakeRecreation |
P8966
|
FINISHED |
| Object | boating on Logan Martin Lake |
—
|
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: boating on Logan Martin Lake | Statement: [Pell City, Alabama, hasLakeRecreation, boating on Logan Martin Lake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeRecreation Context triple: [Pell City, Alabama, hasLakeRecreation, boating on Logan Martin Lake]
-
A.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
B.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
-
C.
recreationAccess
chosen
Indicates that one entity provides or has the ability to use recreational facilities, activities, or spaces associated with another entity.
-
D.
usesLakeFor
Indicates that an entity utilizes a lake as a resource or setting for some purpose, activity, or function.
-
E.
hasBoatRamp
Indicates that a location provides a designated ramp or launch area for putting boats into the water or taking them out.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a748f4c8190bcd868de2fcf0b3a |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae9316e98819080be7bf1a6ff92f1 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:04 p.m.