Triple
T21405210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | And Just Like That... |
E528014
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | David Eigenberg |
—
|
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 Eigenberg | Statement: [And Just Like That..., castMember, David Eigenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Eigenberg Context triple: [And Just Like That..., castMember, David Eigenberg]
-
A.
David Eigenberg
chosen
David Eigenberg is an American actor best known for his role as Steve Brady in the Sex and the City franchise and as Christopher Herrmann on the television series Chicago Fire.
-
B.
Dan Bucatinsky
Dan Bucatinsky is an American actor, writer, and producer best known for his Emmy-winning role on "Scandal" and his work in television comedy and drama.
-
C.
Michael Jaffe
Michael Jaffe is an American television and film producer known for his work on numerous TV movies, series, and feature films.
-
D.
Bob Engelman
Bob Engelman is a film producer best known for working on major Hollywood movies, including the hit comedy "The Mask."
-
E.
Dave Rosenberg
Dave Rosenberg is a technology entrepreneur best known as a co-founder of MuleSoft, a leading integration and API management platform company.
- 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_69e0b520ee3c8190abddbee7e37e834c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b1aea22881909a0cc754e417fbf3 |
completed | April 22, 2026, 11:31 a.m. |
Created at: April 16, 2026, 5:31 p.m.