Triple
T6329133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutty Bomowski |
E141932
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object |
Bomowski
Bomowski is a surname most notably associated with the fictional character Tutty Bomowski.
|
E586716
|
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: Bomowski | Statement: [Tutty Bomowski, hasSurname, Bomowski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bomowski Context triple: [Tutty Bomowski, hasSurname, Bomowski]
-
A.
Bomer
Bomer is the surname of American actor Matt Bomer, known for his roles in television and film such as "White Collar" and "The Normal Heart."
-
B.
Dombrowski
Dombrowski is a surname most prominently associated with Dave Dombrowski, a longtime Major League Baseball executive known for leading multiple franchises to pennants and World Series titles.
-
C.
Bortnowski
Bortnowski is a Polish surname most notably associated with Władysław Bortnowski, a Polish general who served during World War II.
-
D.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
E.
Zaslofsky
Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
- 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: Bomowski Triple: [Tutty Bomowski, hasSurname, Bomowski]
Generated description
Bomowski is a surname most notably associated with the fictional character Tutty Bomowski.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bomowski Target entity description: Bomowski is a surname most notably associated with the fictional character Tutty Bomowski.
-
A.
Bomer
Bomer is the surname of American actor Matt Bomer, known for his roles in television and film such as "White Collar" and "The Normal Heart."
-
B.
Dombrowski
Dombrowski is a surname most prominently associated with Dave Dombrowski, a longtime Major League Baseball executive known for leading multiple franchises to pennants and World Series titles.
-
C.
Bortnowski
Bortnowski is a Polish surname most notably associated with Władysław Bortnowski, a Polish general who served during World War II.
-
D.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
E.
Zaslofsky
Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0651197908190a30e504e2442d40f |
completed | March 22, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604154a1c8190b09e74cea2a18624 |
completed | March 27, 2026, 4:14 a.m. |
| NEDg | Description generation | batch_69c605be33b081908a88b14ffc9b7e45 |
completed | March 27, 2026, 4:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6063391c08190be94743c4c326805 |
completed | March 27, 2026, 4:23 a.m. |
Created at: March 22, 2026, 4:30 p.m.