Triple
T4980056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kismet |
E111860
|
entity |
| Predicate | originalAuthor |
P2806
|
FINISHED |
| Object |
Mike Kershaw
Mike Kershaw is a software developer best known for creating the wireless network detector and sniffer tool Kismet.
|
E484047
|
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: Mike Kershaw | Statement: [Kismet, originalAuthor, Mike Kershaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Kershaw Context triple: [Kismet, originalAuthor, Mike Kershaw]
-
A.
John Briscoe
John Briscoe was a renowned engineer and water resources expert recognized globally for his contributions to water management and policy.
-
B.
Will Halloway
Will Halloway is a thoughtful and courageous young boy who confronts a sinister traveling carnival in Ray Bradbury’s dark fantasy novel "Something Wicked This Way Comes."
-
C.
Jeff Fenech
Jeff Fenech is a former Australian professional boxer and three-division world champion widely regarded as one of his country’s greatest fighters.
-
D.
Scott Shriner
Scott Shriner is an American musician best known as the longtime bassist for the rock band Weezer.
-
E.
Luther Van Dam
Luther Van Dam is a bumbling yet lovable assistant football coach on the sitcom "Coach," known for his comedic antics and loyalty to head coach Hayden Fox.
- 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: Mike Kershaw Triple: [Kismet, originalAuthor, Mike Kershaw]
Generated description
Mike Kershaw is a software developer best known for creating the wireless network detector and sniffer tool Kismet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike Kershaw Target entity description: Mike Kershaw is a software developer best known for creating the wireless network detector and sniffer tool Kismet.
-
A.
John Briscoe
John Briscoe was a renowned engineer and water resources expert recognized globally for his contributions to water management and policy.
-
B.
Will Halloway
Will Halloway is a thoughtful and courageous young boy who confronts a sinister traveling carnival in Ray Bradbury’s dark fantasy novel "Something Wicked This Way Comes."
-
C.
Jeff Fenech
Jeff Fenech is a former Australian professional boxer and three-division world champion widely regarded as one of his country’s greatest fighters.
-
D.
Scott Shriner
Scott Shriner is an American musician best known as the longtime bassist for the rock band Weezer.
-
E.
Luther Van Dam
Luther Van Dam is a bumbling yet lovable assistant football coach on the sitcom "Coach," known for his comedic antics and loyalty to head coach Hayden Fox.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7251b7648190bbb0acf0b9148ae6 |
completed | March 20, 2026, 4:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a0f90048190998dad99555891c0 |
completed | March 21, 2026, 12:07 p.m. |
| NEDg | Description generation | batch_69be8aec16748190922d3b9de523b1ae |
completed | March 21, 2026, 12:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be8b80af18819091efdfe242b7b477 |
completed | March 21, 2026, 12:13 p.m. |
Created at: March 20, 2026, 1:33 p.m.