Triple
T21758112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haines City, Florida |
E537091
|
entity |
| Predicate | hasLake |
P1025
|
FINISHED |
| Object |
Lake Eva
Lake Eva is a freshwater lake and popular recreational spot in Haines City, Florida, known for its adjacent park and community events.
|
E1500563
|
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 Eva | Statement: [Haines City, Florida, hasLake, Lake Eva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Eva Context triple: [Haines City, Florida, hasLake, Lake Eva]
-
A.
Lake Herman
Lake Herman is a natural glacial lake in eastern South Dakota known for recreation such as fishing, boating, and camping within Lake Herman State Park.
-
B.
Lake Arthur
Lake Arthur is a man-made reservoir in western Pennsylvania known for boating, fishing, and other recreational activities within Moraine State Park.
-
C.
Lake Arthur
Lake Arthur is a small town in southeastern New Mexico, located in Chaves County.
-
D.
Lake Kampeska
Lake Kampeska is a natural glacial lake in eastern South Dakota known for recreation, fishing, and lakeside residential development near the city of Watertown.
-
E.
Lake Louisa
Lake Louisa is a large freshwater lake in Central Florida known for its scenic state park, outdoor recreation, and proximity to the city of Clermont.
- 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 Eva Triple: [Haines City, Florida, hasLake, Lake Eva]
Generated description
Lake Eva is a freshwater lake and popular recreational spot in Haines City, Florida, known for its adjacent park and community events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lake Eva Target entity description: Lake Eva is a freshwater lake and popular recreational spot in Haines City, Florida, known for its adjacent park and community events.
-
A.
Lake Herman
Lake Herman is a natural glacial lake in eastern South Dakota known for recreation such as fishing, boating, and camping within Lake Herman State Park.
-
B.
Lake Arthur
Lake Arthur is a man-made reservoir in western Pennsylvania known for boating, fishing, and other recreational activities within Moraine State Park.
-
C.
Lake Arthur
Lake Arthur is a small town in southeastern New Mexico, located in Chaves County.
-
D.
Lake Kampeska
Lake Kampeska is a natural glacial lake in eastern South Dakota known for recreation, fishing, and lakeside residential development near the city of Watertown.
-
E.
Lake Louisa
Lake Louisa is a large freshwater lake in Central Florida known for its scenic state park, outdoor recreation, and proximity to the city of Clermont.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d902c9881908051904e44a136af |
completed | April 28, 2026, 2:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a367268908190a0fd9c8531ea60f1 |
completed | May 17, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_6a0a37b4a00c8190935e7f7fb4c456ca |
completed | May 17, 2026, 9:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a3849dc0881909e5b7c5dd76c56bf |
completed | May 17, 2026, 9:51 p.m. |
Created at: April 16, 2026, 6:50 p.m.