Triple
T15632522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garland Greene |
E375850
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Scott Rosenberg |
E300554
|
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 Rosenberg | Statement: [Garland Greene, createdBy, Scott Rosenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Rosenberg Context triple: [Garland Greene, createdBy, Scott Rosenberg]
-
A.
Scott Rosenberg
chosen
Scott Rosenberg is an American screenwriter and producer known for writing high-profile films such as "Con Air," "Gone in 60 Seconds," and "High Fidelity."
-
B.
Scott Mitchell Rosenberg
Scott Mitchell Rosenberg is an American comic book publisher and film producer best known for founding Malibu Comics and creating the graphic novel that inspired the movie "Cowboys & Aliens."
-
C.
Mark Rosenberg
Mark Rosenberg was an American film producer known for his work on notable movies of the 1980s and early 1990s.
-
D.
Dave Rosenberg
Dave Rosenberg is a technology entrepreneur best known as a co-founder of MuleSoft, a leading integration and API management platform company.
-
E.
Eric Rosen
Eric Rosen is a business executive known for his leadership role as chairman of the automotive company Motor Action.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9321f308190b8101162ed671e5e |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:14 a.m.