Triple
T13454348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Marie Pfaff |
E311189
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Debby Pfaff
Debby Pfaff is a Belgian television personality best known for appearing with her family in the reality series "De Pfaffs."
|
E1057901
|
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: Debby Pfaff | Statement: [Jean-Marie Pfaff, child, Debby Pfaff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Debby Pfaff Context triple: [Jean-Marie Pfaff, child, Debby Pfaff]
-
A.
Debra Frisch
Debra Frisch is an American former psychology professor and blogger best known for a high-profile online harassment case involving a political commentator.
-
B.
Nancy Schafer
Nancy Schafer is a film and television producer known for her work on independent and documentary projects.
-
C.
Paula Braun
Paula Braun is an American health IT and data science expert known for her work modernizing public health surveillance and analytics, including at the U.S. Centers for Disease Control and Prevention (CDC).
-
D.
Rachel Pfeffer
Rachel Pfeffer is a film producer best known for her work on the 2001 romantic drama "Crazy/Beautiful."
-
E.
Debby Wolfe
Debby Wolfe is a television writer and producer best known for creating the NBC sitcom "Lopez vs Lopez" and her work on various comedy series.
- 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: Debby Pfaff Triple: [Jean-Marie Pfaff, child, Debby Pfaff]
Generated description
Debby Pfaff is a Belgian television personality best known for appearing with her family in the reality series "De Pfaffs."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Debby Pfaff Target entity description: Debby Pfaff is a Belgian television personality best known for appearing with her family in the reality series "De Pfaffs."
-
A.
Debra Frisch
Debra Frisch is an American former psychology professor and blogger best known for a high-profile online harassment case involving a political commentator.
-
B.
Nancy Schafer
Nancy Schafer is a film and television producer known for her work on independent and documentary projects.
-
C.
Paula Braun
Paula Braun is an American health IT and data science expert known for her work modernizing public health surveillance and analytics, including at the U.S. Centers for Disease Control and Prevention (CDC).
-
D.
Rachel Pfeffer
Rachel Pfeffer is a film producer best known for her work on the 2001 romantic drama "Crazy/Beautiful."
-
E.
Debby Wolfe
Debby Wolfe is a television writer and producer best known for creating the NBC sitcom "Lopez vs Lopez" and her work on various comedy series.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaefc52448190b30d7999f44a9765 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d37b9988190b8f830fb52586340 |
completed | May 3, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f7a18eb038819089fcbf961a94cb0c |
completed | May 3, 2026, 7:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7a2234390819093814fd435f9c42c |
completed | May 3, 2026, 7:29 p.m. |
Created at: April 9, 2026, 9:41 p.m.