Triple
T3860019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannery Row |
E90111
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
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.
|
E394535
|
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: [Cannery Row, mainCharacter, Doc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doc Context triple: [Cannery Row, 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.
Docter
Docter is the surname of Pete Docter, the acclaimed American animator, director, and key creative figure at Pixar Animation Studios.
-
E.
DOCO
DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
- 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: [Cannery Row, mainCharacter, Doc]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Doc Target entity description: 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.
-
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.
Docter
Docter is the surname of Pete Docter, the acclaimed American animator, director, and key creative figure at Pixar Animation Studios.
-
E.
DOCO
DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1ff39c8190b83a88abd840a0e3 |
completed | March 9, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b512348fe88190b5ae942809732b76 |
completed | March 14, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69b513013db481908f8fb5f56470c0d0 |
completed | March 14, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5137200a08190bd2a78398e03803e |
completed | March 14, 2026, 7:51 a.m. |
Created at: March 9, 2026, 3:19 p.m.