Triple
T6812959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Farmer Takes a Wife |
E156680
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Dan Harrow
Dan Harrow is the earnest, idealistic young farmer who serves as the central romantic lead in the stage musical and film "The Farmer Takes a Wife."
|
E646839
|
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: Dan Harrow | Statement: [The Farmer Takes a Wife, mainCharacter, Dan Harrow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Harrow Context triple: [The Farmer Takes a Wife, mainCharacter, Dan Harrow]
-
A.
Dan Talbot
Dan Talbot was an influential American film distributor and exhibitor known for championing foreign and independent cinema in the United States.
-
B.
Neil Hartley
Neil Hartley is a film and television producer known for his work on the adaptation of "The Go-Between."
-
C.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
D.
Scott Gorham
Scott Gorham is an American guitarist best known for his long tenure with the hard rock band Thin Lizzy and later work with its successor projects.
-
E.
Dan Crow
Dan Crow is an American children's musician and songwriter best known for performing the theme song to the Disney Channel series "Welcome to Pooh Corner."
- 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: Dan Harrow Triple: [The Farmer Takes a Wife, mainCharacter, Dan Harrow]
Generated description
Dan Harrow is the earnest, idealistic young farmer who serves as the central romantic lead in the stage musical and film "The Farmer Takes a Wife."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dan Harrow Target entity description: Dan Harrow is the earnest, idealistic young farmer who serves as the central romantic lead in the stage musical and film "The Farmer Takes a Wife."
-
A.
Dan Talbot
Dan Talbot was an influential American film distributor and exhibitor known for championing foreign and independent cinema in the United States.
-
B.
Neil Hartley
Neil Hartley is a film and television producer known for his work on the adaptation of "The Go-Between."
-
C.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
D.
Scott Gorham
Scott Gorham is an American guitarist best known for his long tenure with the hard rock band Thin Lizzy and later work with its successor projects.
-
E.
Dan Crow
Dan Crow is an American children's musician and songwriter best known for performing the theme song to the Disney Channel series "Welcome to Pooh Corner."
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d329861881909f65bd1017ea384b |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b8a72af081909e5e6da123a47694 |
completed | March 28, 2026, 11:16 a.m. |
| NEDg | Description generation | batch_69c7b9d4d9e081908abc7841371c291b |
completed | March 28, 2026, 11:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ba7c7ac88190b16ba217cdc12325 |
completed | March 28, 2026, 11:24 a.m. |
Created at: March 27, 2026, 2:17 p.m.