Triple
T10355478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Thin Red Line |
E243988
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Billy Weber |
E285441
|
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: Billy Weber | Statement: [The Thin Red Line, editedBy, Billy Weber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billy Weber Context triple: [The Thin Red Line, editedBy, Billy Weber]
-
A.
Billy Weber
chosen
Billy Weber is an American film editor known for his long-time collaboration with director Terrence Malick on critically acclaimed films.
-
B.
Daryl Stuermer
Daryl Stuermer is an American guitarist and bassist best known for his long-time work as a touring and session musician with Genesis and Phil Collins.
-
C.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
D.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
E.
Michael Watts
Michael Watts is a notable individual whose name is associated with the surname Watts, though additional context is needed to distinguish his specific identity or achievements.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e953d4888190b7ca0ac932349dbf |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d750a9b4188190a8ecdd9e4d97570b |
completed | April 9, 2026, 7:09 a.m. |
Created at: April 6, 2026, 11:58 a.m.