Triple
T20231425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piekarski |
E495534
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Daniel Piekarski
Daniel Piekarski is a person notable enough to be recognized as a bearer of the surname Piekarski, though specific widely known public achievements or roles are not clearly documented.
|
E1418672
|
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: Daniel Piekarski | Statement: [Piekarski, hasNotableBearer, Daniel Piekarski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Piekarski Context triple: [Piekarski, hasNotableBearer, Daniel Piekarski]
-
A.
Adrian Piekarski
Adrian Piekarski is a person notable enough to be recognized as a bearer of the surname Piekarski.
-
B.
Kevin Sierzega
Kevin Sierzega is a musician best known as a member of the punk rock band Squirtgun.
-
C.
Edward Kazmierczak
Edward Kazmierczak is a former Polish footballer best known for his time playing for Stal Mielec.
-
D.
Peter Jankowski
Peter Jankowski is a television producer best known for his longtime work on Dick Wolf’s crime drama franchises, including the Chicago and Law & Order series.
-
E.
Tom Jankiewicz
Tom Jankiewicz was an American screenwriter best known for writing the cult dark comedy film "Grosse Pointe Blank."
- 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: Daniel Piekarski Triple: [Piekarski, hasNotableBearer, Daniel Piekarski]
Generated description
Daniel Piekarski is a person notable enough to be recognized as a bearer of the surname Piekarski, though specific widely known public achievements or roles are not clearly documented.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniel Piekarski Target entity description: Daniel Piekarski is a person notable enough to be recognized as a bearer of the surname Piekarski, though specific widely known public achievements or roles are not clearly documented.
-
A.
Adrian Piekarski
chosen
Adrian Piekarski is a person notable enough to be recognized as a bearer of the surname Piekarski.
-
B.
Kevin Sierzega
Kevin Sierzega is a musician best known as a member of the punk rock band Squirtgun.
-
C.
Edward Kazmierczak
Edward Kazmierczak is a former Polish footballer best known for his time playing for Stal Mielec.
-
D.
Peter Jankowski
Peter Jankowski is a television producer best known for his longtime work on Dick Wolf’s crime drama franchises, including the Chicago and Law & Order series.
-
E.
Tom Jankiewicz
Tom Jankiewicz was an American screenwriter best known for writing the cult dark comedy film "Grosse Pointe Blank."
- F. None of above.
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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fddafac819089cef4158f5e0ab5 |
completed | April 20, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a085a15b7848190b55a1e8b52503690 |
completed | May 16, 2026, 11:50 a.m. |
| NEDg | Description generation | batch_6a085a6a94e88190a3f2f2cf89013d44 |
completed | May 16, 2026, 11:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a085aca03748190b3d0544ebda3b8a7 |
completed | May 16, 2026, 11:53 a.m. |
Created at: April 11, 2026, 11:39 p.m.