Triple
T35434597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Shore Park |
E1024165
|
entity |
| Predicate | hasTypeOfWaterfront |
P92288
|
FINISHED |
| Object | Great Lakes shoreline |
—
|
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: Great Lakes shoreline | Statement: [South Shore Park, hasTypeOfWaterfront, Great Lakes shoreline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfWaterfront Context triple: [South Shore Park, hasTypeOfWaterfront, Great Lakes shoreline]
-
A.
hasWaterfrontType
chosen
Indicates that an entity is associated with a specific type or category of waterfront (e.g., oceanfront, lakefront, riverfront).
-
B.
hasWaterfrontLocation
Indicates that an entity is situated directly adjacent to or along a body of water, such as a sea, lake, or river.
-
C.
hasWaterfrontArea
Indicates that an entity possesses or includes an area directly adjacent to or bordering a body of water.
-
D.
isWaterfrontEstate
Indicates that a property is an estate located directly adjacent to a body of water, such as a lake, river, or ocean.
-
E.
isWaterfrontBuilding
Indicates that a building is located directly adjacent to a body of water, such as a river, lake, or ocean.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff7bc112088190851501fb2a16103d |
completed | May 9, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69ff7b45507c81909753866ad733601a |
completed | May 9, 2026, 6:21 p.m. |
Created at: May 3, 2026, 4:04 p.m.