Triple
T18126053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Rappaport |
E433877
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | David Stephen Rappaport |
—
|
NE NERFINISHED |
How this triple was built (2 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: David Stephen Rappaport | Statement: [David Rappaport, birthName, David Stephen Rappaport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Stephen Rappaport Context triple: [David Rappaport, birthName, David Stephen Rappaport]
-
A.
Daniel Rappaport
Daniel Rappaport is a film producer known for working on mainstream Hollywood comedies, including the movie "Office Christmas Party."
-
B.
Sam Rappaport
Sam Rappaport is a fictional character from the soap opera "One Life to Live," known for his complex personal life and romantic entanglements in Llanview.
-
C.
David Rappaport
chosen
David Rappaport was a British actor best known for his roles in fantasy and science-fiction films and television series during the late 20th century.
-
D.
Aaron Rapaport
Aaron Rapaport is a fictional television producer and best friend of talk-show host Dave Skylark in the 2014 comedy film "The Interview."
-
E.
Andrew Rabinovich
Andrew Rabinovich is a computer scientist and researcher known for his contributions to computer vision and deep learning, including influential work at Google.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddee1efc8190b04324b98de5c9d0 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.