Triple
T14943981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soldier Blue |
E372604
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Robert B. Hauser |
—
|
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: Robert B. Hauser | Statement: [Soldier Blue, cinematographyBy, Robert B. Hauser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert B. Hauser Context triple: [Soldier Blue, cinematographyBy, Robert B. Hauser]
-
A.
Robert B. Hauser
chosen
Robert B. Hauser is a cinematographer best known for his work on the film "Gideon's Trumpet."
-
B.
Conrad S. Hauser
Conrad S. Hauser is the real name of Duke, a central G.I. Joe character known as a tough, principled U.S. Army sergeant and field commander in the franchise.
-
C.
Allen G. Siegler
Allen G. Siegler was an American cinematographer active during the early to mid-20th century, known for his work on numerous Hollywood films.
-
D.
Charles B. Wessler
Charles B. Wessler is an American film producer best known for his work on the Academy Award–winning film "Green Book" and various successful comedies.
-
E.
Robert M. Beren
Robert M. Beren is an American businessman and philanthropist known for his significant support of Jewish and educational institutions.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68d20048190a403af85fe43dede |
completed | April 15, 2026, 12:06 a.m. |
Created at: April 10, 2026, 2:38 a.m.