Triple
T10467397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V for Vendetta |
E246831
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Adam Sutler
Adam Sutler is the authoritarian High Chancellor of a dystopian Britain in the graphic novel and film "V for Vendetta," serving as the story’s primary fascist antagonist.
|
E865364
|
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: Adam Sutler | Statement: [V for Vendetta, mainCharacter, Adam Sutler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Sutler Context triple: [V for Vendetta, mainCharacter, Adam Sutler]
-
A.
Mark Suter
Mark Suter is a percussionist known for his work in contemporary and world music, including performances with the Silk Road Ensemble.
-
B.
Kevin Vann
Kevin Vann is an American prelate of the Roman Catholic Church who serves as the bishop of the Diocese of Orange in California.
-
C.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
D.
Tucker Tooley
Tucker Tooley is an American film producer and executive known for backing commercially successful action and thriller movies in Hollywood.
-
E.
Ron Feemster
Ron Feemster is a music producer known for his work on the album "Afrodisiac."
- 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: Adam Sutler Triple: [V for Vendetta, mainCharacter, Adam Sutler]
Generated description
Adam Sutler is the authoritarian High Chancellor of a dystopian Britain in the graphic novel and film "V for Vendetta," serving as the story’s primary fascist antagonist.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adam Sutler Target entity description: Adam Sutler is the authoritarian High Chancellor of a dystopian Britain in the graphic novel and film "V for Vendetta," serving as the story’s primary fascist antagonist.
-
A.
Mark Suter
Mark Suter is a percussionist known for his work in contemporary and world music, including performances with the Silk Road Ensemble.
-
B.
Kevin Vann
Kevin Vann is an American prelate of the Roman Catholic Church who serves as the bishop of the Diocese of Orange in California.
-
C.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
D.
Tucker Tooley
Tucker Tooley is an American film producer and executive known for backing commercially successful action and thriller movies in Hollywood.
-
E.
Ron Feemster
Ron Feemster is a music producer known for his work on the album "Afrodisiac."
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092e3230819098ab444f73c9bd40 |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89ff1cd948190a1ef331fb810bf26 |
completed | April 10, 2026, 7 a.m. |
| NEDg | Description generation | batch_69d8a2b0d8c88190a1a64bd2bbacabbe |
completed | April 10, 2026, 7:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d8a6560ddc81909d540f78a9413b3e |
completed | April 10, 2026, 7:27 a.m. |
Created at: April 6, 2026, 12:20 p.m.