Triple
T20396966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Raven (1935 film) |
E500230
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | David Boehm |
—
|
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: David Boehm | Statement: [The Raven (1935 film), screenwriter, David Boehm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Boehm Context triple: [The Raven (1935 film), screenwriter, David Boehm]
-
A.
David Boehm
chosen
David Boehm was an American screenwriter active during Hollywood’s early sound era, known for contributing to several popular studio films of the 1930s.
-
B.
Richard P. Gabriel
Richard P. Gabriel is a computer scientist and writer best known for his work on Lisp, software patterns, and his influential essay "Worse Is Better."
-
C.
Michael Goguen
Michael Goguen is an American animation producer and director best known for his work on numerous superhero and action-oriented animated television series.
-
D.
David Garlan
David Garlan is a computer scientist known for his influential work in software architecture and formal modeling of software systems.
-
E.
Jack Schwartz
Jack Schwartz was an American mathematician and computer scientist known for his contributions to programming languages, parallel computing, and the development of the SETL language.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6798b6640819085d5b12dc35633fe |
completed | April 20, 2026, 7:07 p.m. |
Created at: April 16, 2026, 11:28 a.m.