Triple
T626329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Park, Maryland |
E15826
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Lakeland
Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
|
E107660
|
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: Lakeland | Statement: [College Park, Maryland, hasNeighborhood, Lakeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakeland Context triple: [College Park, Maryland, hasNeighborhood, Lakeland]
-
A.
Kissimmee, Florida
Kissimmee, Florida is a central Florida city in Osceola County known for its proximity to major Orlando-area theme parks and tourist attractions.
-
B.
Bagdad, Florida
Bagdad, Florida is a small unincorporated community and historic mill town located along the Blackwater River in the Florida Panhandle.
-
C.
Sarasota, Florida
Sarasota, Florida is a Gulf Coast city known for its beaches, arts and cultural scene, and as a longtime hub for Major League Baseball spring training.
-
D.
Homestead, Florida
Homestead, Florida is a small city in Miami-Dade County known as an agricultural hub and gateway to both Everglades and Biscayne National Parks.
-
E.
Orlando
Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
- 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: Lakeland Triple: [College Park, Maryland, hasNeighborhood, Lakeland]
Generated description
Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lakeland Target entity description: Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
-
A.
Kissimmee, Florida
Kissimmee, Florida is a central Florida city in Osceola County known for its proximity to major Orlando-area theme parks and tourist attractions.
-
B.
Bagdad, Florida
Bagdad, Florida is a small unincorporated community and historic mill town located along the Blackwater River in the Florida Panhandle.
-
C.
Sarasota, Florida
Sarasota, Florida is a Gulf Coast city known for its beaches, arts and cultural scene, and as a longtime hub for Major League Baseball spring training.
-
D.
Homestead, Florida
Homestead, Florida is a small city in Miami-Dade County known as an agricultural hub and gateway to both Everglades and Biscayne National Parks.
-
E.
Orlando
Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e587c448190987943a6aad209d1 |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c7074cc88190912969a1ba0a8c6e |
completed | March 4, 2026, 5:45 a.m. |
| NEDg | Description generation | batch_69a7cb421ef08190817648ff69923160 |
completed | March 4, 2026, 6:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7cb9f001881909164cf19b0c86f32 |
completed | March 4, 2026, 6:05 a.m. |
Created at: March 1, 2026, 7:35 p.m.