Triple
T14747013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FlowRider |
E346498
|
entity |
| Predicate | hasCreator |
P806
|
FINISHED |
| Object |
Tom Lochtefeld
Tom Lochtefeld is an American inventor and entrepreneur best known for pioneering modern surf-simulation attractions and waterpark wave technologies.
|
E1117954
|
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: Tom Lochtefeld | Statement: [FlowRider, hasCreator, Tom Lochtefeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Lochtefeld Context triple: [FlowRider, hasCreator, Tom Lochtefeld]
-
A.
Phil Leotardo
Phil Leotardo is a ruthless New York mob boss and major antagonist in the television series "The Sopranos."
-
B.
Luke Del Tredici
Luke Del Tredici is a television writer and producer best known for his work on the comedy series "Brooklyn Nine-Nine."
-
C.
Michael Lohan
Michael Lohan is an American television personality and businessman best known as the often-controversial father of actress and singer Lindsay Lohan.
-
D.
Tom Lofaro
Tom Lofaro is a television producer best known for his executive production work on the long-running comedy series "It's Always Sunny in Philadelphia."
-
E.
Tom Dula
Tom Dula was a North Carolina man whose 1868 execution for the murder of Laura Foster inspired the famous American folk ballad "Tom Dooley."
- 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: Tom Lochtefeld Triple: [FlowRider, hasCreator, Tom Lochtefeld]
Generated description
Tom Lochtefeld is an American inventor and entrepreneur best known for pioneering modern surf-simulation attractions and waterpark wave technologies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Lochtefeld Target entity description: Tom Lochtefeld is an American inventor and entrepreneur best known for pioneering modern surf-simulation attractions and waterpark wave technologies.
-
A.
Phil Leotardo
Phil Leotardo is a ruthless New York mob boss and major antagonist in the television series "The Sopranos."
-
B.
Luke Del Tredici
Luke Del Tredici is a television writer and producer best known for his work on the comedy series "Brooklyn Nine-Nine."
-
C.
Michael Lohan
Michael Lohan is an American television personality and businessman best known as the often-controversial father of actress and singer Lindsay Lohan.
-
D.
Tom Lofaro
Tom Lofaro is a television producer best known for his executive production work on the long-running comedy series "It's Always Sunny in Philadelphia."
-
E.
Tom Dula
Tom Dula was a North Carolina man whose 1868 execution for the murder of Laura Foster inspired the famous American folk ballad "Tom Dooley."
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d116e88190828b163b18d80f68 |
completed | April 14, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb982b5c8190a0340be2186f8b81 |
completed | May 8, 2026, 3:04 p.m. |
| NEDg | Description generation | batch_69fdfea2b720819089110c02dbd848bd |
completed | May 8, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdff1368e48190bc079645996d85d8 |
completed | May 8, 2026, 3:19 p.m. |
Created at: April 10, 2026, 1:30 a.m.