Triple
T5557918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Kingdom of Love (1917 film) |
E145692
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Charles Arling
Charles Arling was a Canadian-born silent film actor active in early 20th-century American cinema.
|
E542786
|
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: Charles Arling | Statement: [The Kingdom of Love (1917 film), hasCastMember, Charles Arling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Arling Context triple: [The Kingdom of Love (1917 film), hasCastMember, Charles Arling]
-
A.
John Gibbon
John Gibbon was a 19th-century United States Army officer and Civil War general who later played a key role in the Indian Wars, including campaigns against the Nez Perce.
-
B.
Jon Hensley
Jon Hensley is an American actor best known for his long-running role as Holden Snyder on the soap opera "As the World Turns."
-
C.
George Sowards
George Sowards is an actor known for his role in the film "Shotgun."
-
D.
Ross Miner
Ross Miner is an American figure skater known for winning multiple U.S. national medals and competing internationally in men's singles.
-
E.
Ray Wise
Ray Wise is an American character actor known for his versatile roles in film and television, including memorable performances in "Twin Peaks," "RoboCop," and numerous other genre and dramatic works.
- 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: Charles Arling Triple: [The Kingdom of Love (1917 film), hasCastMember, Charles Arling]
Generated description
Charles Arling was a Canadian-born silent film actor active in early 20th-century American cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charles Arling Target entity description: Charles Arling was a Canadian-born silent film actor active in early 20th-century American cinema.
-
A.
John Gibbon
John Gibbon was a 19th-century United States Army officer and Civil War general who later played a key role in the Indian Wars, including campaigns against the Nez Perce.
-
B.
Jon Hensley
Jon Hensley is an American actor best known for his long-running role as Holden Snyder on the soap opera "As the World Turns."
-
C.
George Sowards
George Sowards is an actor known for his role in the film "Shotgun."
-
D.
Ross Miner
Ross Miner is an American figure skater known for winning multiple U.S. national medals and competing internationally in men's singles.
-
E.
Ray Wise
Ray Wise is an American character actor known for his versatile roles in film and television, including memorable performances in "Twin Peaks," "RoboCop," and numerous other genre and dramatic works.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0201529a88190bf0135e032b048ea |
completed | March 22, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07d7658a481909e9e9b29df2b148e |
completed | March 22, 2026, 11:38 p.m. |
| NEDg | Description generation | batch_69c08a0906608190a5006b64820dfb51 |
completed | March 23, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08a639b6c8190820fee2c8c43e4d6 |
completed | March 23, 2026, 12:33 a.m. |
Created at: March 22, 2026, 3:36 p.m.