Triple
T16673242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 88 Fingers Louie |
E405155
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Dan Wleklinski
Dan Wleklinski is an American punk rock guitarist best known for his work with the Chicago band 88 Fingers Louie and later Rise Against, where he performed under the name Mr. Precision.
|
E1231724
|
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: Dan Wleklinski | Statement: [88 Fingers Louie, hasMember, Dan Wleklinski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Wleklinski Context triple: [88 Fingers Louie, hasMember, Dan Wleklinski]
-
A.
Eric Dapkewicz
Eric Dapkewicz is a film editor best known for his work on major animated features, including DreamWorks Animation’s "Puss in Boots."
-
B.
Dan Swietlik
Dan Swietlik is a film editor best known for his work on the Academy Award–winning climate change documentary "An Inconvenient Truth."
-
C.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
D.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
E.
Tom Witzky
Tom Witzky is a working-class Chicago lineman whose sudden psychic visions drive the supernatural mystery at the heart of the film "Stir of Echoes."
- 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: Dan Wleklinski Triple: [88 Fingers Louie, hasMember, Dan Wleklinski]
Generated description
Dan Wleklinski is an American punk rock guitarist best known for his work with the Chicago band 88 Fingers Louie and later Rise Against, where he performed under the name Mr. Precision.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dan Wleklinski Target entity description: Dan Wleklinski is an American punk rock guitarist best known for his work with the Chicago band 88 Fingers Louie and later Rise Against, where he performed under the name Mr. Precision.
-
A.
Eric Dapkewicz
Eric Dapkewicz is a film editor best known for his work on major animated features, including DreamWorks Animation’s "Puss in Boots."
-
B.
Dan Swietlik
Dan Swietlik is a film editor best known for his work on the Academy Award–winning climate change documentary "An Inconvenient Truth."
-
C.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
D.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
E.
Tom Witzky
Tom Witzky is a working-class Chicago lineman whose sudden psychic visions drive the supernatural mystery at the heart of the film "Stir of Echoes."
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca276848190b7562d7cb88d21e0 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a50edea48190b65f4e6a9eb3ba24 |
completed | May 10, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a00a5b3ce848190a73f06d9708bfc85 |
completed | May 10, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00a6734d008190bb0a5aa28826e73a |
completed | May 10, 2026, 3:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.