Triple
T11037092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salvation |
E260913
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Craig Shapiro |
E911011
|
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: Craig Shapiro | Statement: [Salvation, executiveProducer, Craig Shapiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Shapiro Context triple: [Salvation, executiveProducer, Craig Shapiro]
-
A.
Craig Shapiro
chosen
Craig Shapiro is a television writer and producer best known for co-creating and showrunning series such as the sci-fi drama "Salvation."
-
B.
Greg Shapiro
Greg Shapiro is an American film producer best known for his Academy Award-winning work on "The Hurt Locker" and other notable independent and studio films.
-
C.
Mark Shapiro
Mark Shapiro is an American media executive and sports industry leader who serves as president and a top decision-maker at Endeavor Group Holdings.
-
D.
Gregory H. Shapiro
Gregory H. Shapiro is an American film producer known for his work on critically acclaimed dramas and independent films, including the Oscar-winning "The Hurt Locker."
-
E.
Todd Lieberman
Todd Lieberman is an American film producer known for his work on acclaimed movies such as "The Fighter" and other major Hollywood productions.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797e9e3fc8190802195ac9fcb8e28 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4acc9d60c819084e342076fe682fc |
completed | April 19, 2026, 10:22 a.m. |
Created at: April 8, 2026, 9:25 p.m.