Triple
T5321522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stablemates (1938 film) |
E121683
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Doc
Doc is the central character in the 1938 horse-racing drama film "Stablemates," around whom the story’s key events and relationships revolve.
|
E512216
|
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: Doc | Statement: [Stablemates (1938 film), mainCharacter, Doc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doc Context triple: [Stablemates (1938 film), mainCharacter, Doc]
-
A.
Doc
Doc is the widely used nickname of Glenn "Doc" Rivers, a former NBA player and championship-winning head coach.
-
B.
Doc
Doc is the nickname of Dwight Gooden, a dominant Major League Baseball pitcher best known for his stellar early career with the New York Mets in the 1980s.
-
C.
Doc
Doc is one of the seven dwarfs in Disney's "Snow White and the Seven Dwarfs," characterized as their kindly, bearded leader who often fumbles his words.
-
D.
Doc
Doc is a gentle, eccentric marine biologist in John Steinbeck’s novel "Cannery Row," known for his intelligence, compassion, and central role in the community’s life.
-
E.
Doc
Doc is the longtime play-by-play announcer Mike "Doc" Emrick, renowned for his iconic voice and decades of work calling National Hockey League games.
- 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: Doc Triple: [Stablemates (1938 film), mainCharacter, Doc]
Generated description
Doc is the central character in the 1938 horse-racing drama film "Stablemates," around whom the story’s key events and relationships revolve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Doc Target entity description: Doc is the central character in the 1938 horse-racing drama film "Stablemates," around whom the story’s key events and relationships revolve.
-
A.
Doc
Doc is a gentle, eccentric marine biologist in John Steinbeck’s novel "Cannery Row," known for his intelligence, compassion, and central role in the community’s life.
-
B.
Doc
Doc is one of the seven dwarfs in Disney's "Snow White and the Seven Dwarfs," characterized as their kindly, bearded leader who often fumbles his words.
-
C.
Doc
Doc is the nickname of Doc Watson, the influential American guitarist and singer known for his flatpicking and folk, bluegrass, and country music.
-
D.
Doc
Doc is the nickname of Dwight Gooden, a dominant Major League Baseball pitcher best known for his stellar early career with the New York Mets in the 1980s.
-
E.
Doc
Doc is the longtime play-by-play announcer Mike "Doc" Emrick, renowned for his iconic voice and decades of work calling National Hockey League games.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85761ec48190879210af116ed8b9 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18a4dff48190bce18f0106c7a8e7 |
completed | March 21, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_69bf1a493ddc8190ac5d1889b9d64ec2 |
completed | March 21, 2026, 10:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf1aa2fbec819088cd8be8505e4697 |
completed | March 21, 2026, 10:24 p.m. |
Created at: March 20, 2026, 1:59 p.m.