Triple
T11328910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Road to El Dorado |
E268293
|
entity |
| Predicate | storyBy |
P1955
|
FINISHED |
| Object |
Will Finn
Will Finn is an American animator, director, and screenwriter known for his work on numerous animated films, including contributions to major Disney productions.
|
E919430
|
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: Will Finn | Statement: [The Road to El Dorado, storyBy, Will Finn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Finn Context triple: [The Road to El Dorado, storyBy, Will Finn]
-
A.
Finis Conner
Finis Conner is an American entrepreneur best known as a pioneering figure in the hard disk drive industry and co-founder of both Seagate Technology and Conner Peripherals.
-
B.
Lucas
Lucas is the surname of George Lucas, the influential American filmmaker best known as the creator of the Star Wars and Indiana Jones franchises.
-
C.
Lucas
Lucas is a prominent former player for the Ohio State Buckeyes men's basketball program, recognized as one of the team's standout athletes.
-
D.
Lucas
Lucas is a 1986 coming-of-age drama film best known for featuring one of Winona Ryder’s earliest prominent screen roles.
-
E.
Lucas
Lucas is the Latin form of the name Luke, traditionally associated with St. Luke the Evangelist in Christian tradition.
- 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: Will Finn Triple: [The Road to El Dorado, storyBy, Will Finn]
Generated description
Will Finn is an American animator, director, and screenwriter known for his work on numerous animated films, including contributions to major Disney productions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Will Finn Target entity description: Will Finn is an American animator, director, and screenwriter known for his work on numerous animated films, including contributions to major Disney productions.
-
A.
Finis Conner
Finis Conner is an American entrepreneur best known as a pioneering figure in the hard disk drive industry and co-founder of both Seagate Technology and Conner Peripherals.
-
B.
Lucas
Lucas is the surname of George Lucas, the influential American filmmaker best known as the creator of the Star Wars and Indiana Jones franchises.
-
C.
Lucas
Lucas is a prominent former player for the Ohio State Buckeyes men's basketball program, recognized as one of the team's standout athletes.
-
D.
Lucas
Lucas is a 1986 coming-of-age drama film best known for featuring one of Winona Ryder’s earliest prominent screen roles.
-
E.
Lucas
Lucas is the Latin form of the name Luke, traditionally associated with St. Luke the Evangelist in Christian tradition.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e330008190b75490efde01dc59 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5261770ac8190b8fc7e2099aa8ace |
completed | April 19, 2026, 6:59 p.m. |
| NEDg | Description generation | batch_69e52c83768c819086ebfd870ad81998 |
completed | April 19, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e531c2a4b88190bb1efd57536bae9a |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:32 p.m.