Triple
T5692734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The L Word |
E125463
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Ralph Winter
Ralph Winter is an American film and television producer best known for his work on major studio franchises such as the X-Men series and other high-profile genre projects.
|
E377151
|
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: Ralph Winter | Statement: [The L Word, executiveProducer, Ralph Winter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Winter Context triple: [The L Word, executiveProducer, Ralph Winter]
-
A.
Ralph Winter
Ralph Winter is an American film producer best known for his work on major genre franchises such as the X-Men series and the Star Trek films.
-
B.
Ralph Stein
Ralph Stein was an American cartoonist, illustrator, and author best known for his work on the comic strip "Popeye" and for his books on World War II and automobiles.
-
C.
Ralph Arnold
Ralph Arnold is the name of several notable individuals, including figures in fields such as geology, engineering, and the arts.
-
D.
Ralph Frost
Ralph Frost is an individual notable enough to be recognized as a bearer of the surname Frost.
-
E.
Ralph Hart
Ralph Hart is an actor best known for his role on the classic American television sitcom "The Lucy Show."
- 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: Ralph Winter Triple: [The L Word, executiveProducer, Ralph Winter]
Generated description
Ralph Winter is an American film and television producer best known for his work on major studio franchises such as the X-Men series and other high-profile genre projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ralph Winter Target entity description: Ralph Winter is an American film and television producer best known for his work on major studio franchises such as the X-Men series and other high-profile genre projects.
-
A.
Ralph Winter
chosen
Ralph Winter is an American film producer best known for his work on major genre franchises such as the X-Men series and the Star Trek films.
-
B.
Ralph Stein
Ralph Stein was an American cartoonist, illustrator, and author best known for his work on the comic strip "Popeye" and for his books on World War II and automobiles.
-
C.
Ralph Arnold
Ralph Arnold is the name of several notable individuals, including figures in fields such as geology, engineering, and the arts.
-
D.
Ralph Frost
Ralph Frost is an individual notable enough to be recognized as a bearer of the surname Frost.
-
E.
Ralph Hart
Ralph Hart is an actor best known for his role on the classic American television sitcom "The Lucy Show."
- F. None of above.
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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e678c48190824d35d276985311 |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1133b6ce0819080ec5d6bad6d2e97 |
completed | March 23, 2026, 10:17 a.m. |
| NEDg | Description generation | batch_69c11511b2b48190a47f1152f7aef2ad |
completed | March 23, 2026, 10:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1156a67548190be763bef22ae7d03 |
completed | March 23, 2026, 10:26 a.m. |
Created at: March 22, 2026, 3:44 p.m.