Triple
T17247573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Christmas |
E418666
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
James Cooper
James Cooper is a film editor known for his work on the animated Christmas movie "Arthur Christmas."
|
E1259212
|
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: James Cooper | Statement: [Arthur Christmas, editedBy, James Cooper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Cooper Context triple: [Arthur Christmas, editedBy, James Cooper]
-
A.
James Cooper
James Cooper is a businessman best known for owning the Philadelphia Blazers franchise in the World Hockey Association.
-
B.
J. G. Cooper
J. G. Cooper was a 19th-century American physician and naturalist known for his influential work in zoology and contributions to the scientific exploration of the western United States.
-
C.
Samuel Cooper
Samuel Cooper was a senior Confederate general who served as the highest-ranking officer and Adjutant and Inspector General of the Confederate States Army during the American Civil War.
-
D.
James Sibley
James Sibley was a benefactor whose contributions to healthcare led to a major Washington, D.C. hospital being named in his honor.
-
E.
Charles Maclay
Charles Maclay was a 19th-century American politician, land developer, and founder of the city of San Fernando in California.
- 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: James Cooper Triple: [Arthur Christmas, editedBy, James Cooper]
Generated description
James Cooper is a film editor known for his work on the animated Christmas movie "Arthur Christmas."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: James Cooper Target entity description: James Cooper is a film editor known for his work on the animated Christmas movie "Arthur Christmas."
-
A.
James Cooper
James Cooper is a businessman best known for owning the Philadelphia Blazers franchise in the World Hockey Association.
-
B.
J. G. Cooper
J. G. Cooper was a 19th-century American physician and naturalist known for his influential work in zoology and contributions to the scientific exploration of the western United States.
-
C.
Samuel Cooper
Samuel Cooper was a senior Confederate general who served as the highest-ranking officer and Adjutant and Inspector General of the Confederate States Army during the American Civil War.
-
D.
James Sibley
James Sibley was a benefactor whose contributions to healthcare led to a major Washington, D.C. hospital being named in his honor.
-
E.
Charles Maclay
Charles Maclay was a 19th-century American politician, land developer, and founder of the city of San Fernando in California.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e24a4508190bbcc70c36b2b9c13 |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170f744d8819099f10bbba364586d |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a01726ae14081909d11434e378d3e1c |
completed | May 11, 2026, 6:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a017525d8108190b2fff7d96beff345 |
completed | May 11, 2026, 6:20 a.m. |
Created at: April 10, 2026, 5:39 a.m.