Triple
T11171178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Young Riders |
E264275
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Ty Miller
Ty Miller is an American actor best known for his role as The Kid in the television western series "The Young Riders."
|
E911101
|
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: Ty Miller | Statement: [The Young Riders, hasCastMember, Ty Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ty Miller Context triple: [The Young Riders, hasCastMember, Ty Miller]
-
A.
JP Miller
JP Miller was an American screenwriter and playwright best known for his hard-hitting television dramas and the film adaptation of "Days of Wine and Roses."
-
B.
Carl Miller
Carl Miller was an American silent film actor active in the 1920s, known for his supporting roles in several notable early Hollywood productions.
-
C.
Robert Lane Miller
Robert Lane Miller is an American author and legal expert known for his work on international business law and cross-border transactions.
-
D.
Fred Miller
Fred Miller is a former American football offensive tackle best known for his NFL career with teams including the St. Louis Rams and Chicago Bears.
-
E.
Sidney Miller
Sidney Miller was a person significant enough in the history or founding of Millerton, New York, that the village was named in his honor.
- 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: Ty Miller Triple: [The Young Riders, hasCastMember, Ty Miller]
Generated description
Ty Miller is an American actor best known for his role as The Kid in the television western series "The Young Riders."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ty Miller Target entity description: Ty Miller is an American actor best known for his role as The Kid in the television western series "The Young Riders."
-
A.
JP Miller
JP Miller was an American screenwriter and playwright best known for his hard-hitting television dramas and the film adaptation of "Days of Wine and Roses."
-
B.
Carl Miller
Carl Miller was an American silent film actor active in the 1920s, known for his supporting roles in several notable early Hollywood productions.
-
C.
Robert Lane Miller
Robert Lane Miller is an American author and legal expert known for his work on international business law and cross-border transactions.
-
D.
Fred Miller
Fred Miller is a former American football offensive tackle best known for his NFL career with teams including the St. Louis Rams and Chicago Bears.
-
E.
Sidney Miller
Sidney Miller was a person significant enough in the history or founding of Millerton, New York, that the village was named in his honor.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e89660208190b1d9e91529f5d246 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e496d1ffa48190b29b4d4b71803564 |
completed | April 19, 2026, 8:48 a.m. |
| NEDg | Description generation | batch_69e49d37989881909c7e75ddfff06726 |
completed | April 19, 2026, 9:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e49f41a1f8819087cc15527dc7ff63 |
completed | April 19, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.