Triple
T1365461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burke Lake Park |
E29191
|
entity |
| Predicate | lakeArea |
P27499
|
FINISHED |
| Object | approximately 218 acres |
—
|
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: approximately 218 acres | Statement: [Burke Lake Park, lakeArea, approximately 218 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lakeArea Context triple: [Burke Lake Park, lakeArea, approximately 218 acres]
-
A.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
B.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
C.
largestLakeEntirelyIn
Indicates that one entity is the largest lake located entirely within the boundaries of another entity (such as a country, region, or territory).
-
D.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
E.
lakeShape
Indicates the geometric or physical outline/form that a lake possesses.
- F. None of above. chosen
Provenance (4 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b725248190bdfdc0031ddc477f |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:57 p.m.