Triple
T2521112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Real World |
E55523
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Jersey Shore |
E21615
|
NE 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: Jersey Shore | Statement: [The Real World, influenced, Jersey Shore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jersey Shore Context triple: [The Real World, influenced, Jersey Shore]
-
A.
Jersey Shore
chosen
Jersey Shore is a popular coastal region along the Atlantic Ocean in New Jersey known for its beaches, boardwalks, and seaside resort towns.
-
B.
The Hills
The Hills is an artificial parkland on Governors Island in New York Harbor featuring landscaped slopes, walking paths, and elevated viewpoints of the city skyline and Statue of Liberty.
-
C.
Outlet Beach
Outlet Beach is a popular sandy swimming beach located within Sandbanks Provincial Park in Ontario, Canada.
-
D.
Sunset Beach
Sunset Beach is a famous North Shore Oahu surf spot known for its massive winter waves and picturesque sunsets.
-
E.
O-Town
O-Town is a popular nickname for the city of Orlando, Florida, often used in local culture and media.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2367b6c819094239dfd12399643 |
completed | March 7, 2026, 7:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2ba64390819083ea639eb4c1a1bd |
completed | March 9, 2026, 8:20 p.m. |
Created at: March 6, 2026, 9:46 p.m.