Triple
T11624662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Hornberger |
E276231
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Scott Adsit |
E326245
|
NE FINISHED |
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: Scott Adsit | Statement: [Pete Hornberger, portrayedBy, Scott Adsit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Adsit Context triple: [Pete Hornberger, portrayedBy, Scott Adsit]
-
A.
Scott Adsit
chosen
Scott Adsit is an American actor and comedian best known for his role as producer Pete Hornberger on the television series "30 Rock."
-
B.
Paul F. Tompkins
Paul F. Tompkins is an American comedian, actor, and writer known for his stand-up, podcast appearances, and character roles in television and film.
-
C.
B. J. Novak
B. J. Novak is an American actor, writer, comedian, and director best known for his work on the U.S. version of "The Office."
-
D.
Nick Kroll
Nick Kroll is an American comedian, actor, writer, and producer known for his sketch series "Kroll Show," his work on "The League," and co-creating and voicing characters in the animated series "Big Mouth."
-
E.
Rob Corddry
Rob Corddry is an American actor and comedian best known for his work on "The Daily Show" and in films like "Hot Tub Time Machine."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a12416908190ac2dcd7f7ebb308f |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee87745b388190a78958fa0c08b89b |
completed | April 26, 2026, 9:45 p.m. |
Created at: April 8, 2026, 9:39 p.m.