Triple
T10391449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Red One |
E244900
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Morton Tubor
Morton Tubor was an American film and sound editor known for his work on notable films including the war epic "The Big Red One."
|
E858973
|
NE FINISHED |
How this triple was built (4 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: Morton Tubor | Statement: [The Big Red One, editedBy, Morton Tubor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morton Tubor Context triple: [The Big Red One, editedBy, Morton Tubor]
-
A.
Tex Johnson
Tex Johnson is a musician known for being a member of the blues-rock supergroup Derek and the Dominos.
-
B.
Gopher Smith
Gopher Smith is a bumbling yet lovable ship’s purser on the classic American television series "The Love Boat."
-
C.
Charlie Sitton
Charlie Sitton is a former American college basketball standout best known for his All-American career at Oregon State University in the early 1980s.
-
D.
Eugene Worley
Eugene Worley was an American jurist who served as a prominent judge on the United States Court of Customs and Patent Appeals.
-
E.
Roger Barton
Roger Barton is a film editor known for his work on major Hollywood blockbusters, including entries in the Star Wars and Transformers franchises.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Morton Tubor Triple: [The Big Red One, editedBy, Morton Tubor]
Generated description
Morton Tubor was an American film and sound editor known for his work on notable films including the war epic "The Big Red One."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Morton Tubor Target entity description: Morton Tubor was an American film and sound editor known for his work on notable films including the war epic "The Big Red One."
-
A.
Tex Johnson
Tex Johnson is a musician known for being a member of the blues-rock supergroup Derek and the Dominos.
-
B.
Gopher Smith
Gopher Smith is a bumbling yet lovable ship’s purser on the classic American television series "The Love Boat."
-
C.
Charlie Sitton
Charlie Sitton is a former American college basketball standout best known for his All-American career at Oregon State University in the early 1980s.
-
D.
Eugene Worley
Eugene Worley was an American jurist who served as a prominent judge on the United States Court of Customs and Patent Appeals.
-
E.
Roger Barton
Roger Barton is a film editor known for his work on major Hollywood blockbusters, including entries in the Star Wars and Transformers franchises.
- F. None of above. chosen
Provenance (5 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b5b43081908641a5abfb08dc2b |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d795b9974c819087340adc3622279e |
completed | April 9, 2026, 12:04 p.m. |
| NEDg | Description generation | batch_69d7985e7fc081909fd1ba1dc6f7338c |
completed | April 9, 2026, 12:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d799917ab881909a947ad8059652c6 |
completed | April 9, 2026, 12:20 p.m. |
Created at: April 6, 2026, 12:06 p.m.