Triple
T5960542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letters from Iwo Jima |
E132624
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Tom Stern |
E203049
|
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: Tom Stern | Statement: [Letters from Iwo Jima, cinematographyBy, Tom Stern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Stern Context triple: [Letters from Iwo Jima, cinematographyBy, Tom Stern]
-
A.
Tom Stern
chosen
Tom Stern is an American cinematographer best known for his frequent collaborations with director Clint Eastwood on numerous acclaimed films.
-
B.
Steve Kirsch
Steve Kirsch is an American entrepreneur and inventor best known for founding multiple technology companies, including the early internet search engine Infoseek.
-
C.
Jeff Pinkner
Jeff Pinkner is an American television writer and producer known for his work on series such as "Fringe," "Alias," and "Lost."
-
D.
Mark Friedman
Mark Friedman is a television writer and producer best known for his work as an executive producer and showrunner on series such as "Severance."
-
E.
Jay Stern
Jay Stern is a film producer best known for his work on mainstream Hollywood comedies, including the hit movie "Horrible Bosses."
- 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c039fd6dd48190a6020bef38b1be82 |
completed | March 22, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3e8f234819099336503a797e55b |
completed | March 23, 2026, 6:55 a.m. |
Created at: March 22, 2026, 4:02 p.m.