Triple
T12422801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milwaukee County Parks |
E296818
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Lake Park
Lake Park is a historic, Frederick Law Olmsted–designed public park in Milwaukee, Wisconsin, known for its scenic bluffs, trails, and views of Lake Michigan.
|
E983045
|
NE FINISHED |
How this triple was built (4 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: Lake Park | Statement: [Milwaukee County Parks, hasPart, Lake Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Park Context triple: [Milwaukee County Parks, hasPart, Lake Park]
-
A.
Lake Park
Lake Park is a public recreational park in Winona, Minnesota, known for its lakeside setting and outdoor amenities.
-
B.
Lake Park
Lake Park is a recreational lakefront park in Des Plaines, Illinois, known for its scenic water views, boating, and outdoor leisure activities.
-
C.
Como Lake Park
Como Lake Park is a scenic urban park in Coquitlam, British Columbia, centered around a small lake and popular for walking, picnicking, and fishing.
-
D.
Bay Lake
Bay Lake is a natural lake in Central Florida located near the Walt Disney World Resort.
-
E.
Round Lake
Round Lake is a small village and lake in Saratoga County, New York, known for its historic character and recreational waterfront.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lake Park Triple: [Milwaukee County Parks, hasPart, Lake Park]
Generated description
Lake Park is a historic, Frederick Law Olmsted–designed public park in Milwaukee, Wisconsin, known for its scenic bluffs, trails, and views of Lake Michigan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lake Park Target entity description: Lake Park is a historic, Frederick Law Olmsted–designed public park in Milwaukee, Wisconsin, known for its scenic bluffs, trails, and views of Lake Michigan.
-
A.
Lake Park
Lake Park is a recreational lakefront park in Des Plaines, Illinois, known for its scenic water views, boating, and outdoor leisure activities.
-
B.
Lake Park
Lake Park is a public recreational park in Winona, Minnesota, known for its lakeside setting and outdoor amenities.
-
C.
Como Lake Park
Como Lake Park is a scenic urban park in Coquitlam, British Columbia, centered around a small lake and popular for walking, picnicking, and fishing.
-
D.
Bay Lake
Bay Lake is a natural lake in Central Florida located near the Walt Disney World Resort.
-
E.
Round Lake
Round Lake is a small, roughly circular lake in Illinois that lends its name to the surrounding village of Round Lake.
- F. None of above. chosen
Provenance (5 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d702b1481909db5f5bed6292ce0 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f0265fc81909a6288d11b78c2f9 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f6403711bc8190b214d4b06792a538 |
completed | May 2, 2026, 6:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f640f543c08190b95b16a8909eebf8 |
completed | May 2, 2026, 6:22 p.m. |
Created at: April 8, 2026, 9:55 p.m.