Triple
T13933497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2 Guns |
E335049
|
entity |
| Predicate | basedOnWorkAuthor |
P2806
|
FINISHED |
| Object |
Steven Grant
Steven Grant is an American comic book writer best known for creating the graphic novel that inspired the film "2 Guns."
|
E1069934
|
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: Steven Grant | Statement: [2 Guns, basedOnWorkAuthor, Steven Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steven Grant Context triple: [2 Guns, basedOnWorkAuthor, Steven Grant]
-
A.
Steven Grant
Steven Grant is one of the main identities of the Marvel Comics character Moon Knight, portrayed in the Marvel Cinematic Universe by Oscar Isaac.
-
B.
Arthur Grant
Arthur Grant was a British cinematographer best known for his work on numerous Hammer Films productions in the mid-20th century.
-
C.
Michael Graydon
Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
-
D.
Nick Grindé
Nick Grindé was a screenwriter active during early Hollywood cinema, known for contributing to films such as the 1930 drama "The Divorcee."
-
E.
Jonathan Scott
Jonathan Scott is a wildlife photographer and television presenter best known for his work on BBC nature documentaries, particularly those focusing on big cats in Africa.
- 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: Steven Grant Triple: [2 Guns, basedOnWorkAuthor, Steven Grant]
Generated description
Steven Grant is an American comic book writer best known for creating the graphic novel that inspired the film "2 Guns."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steven Grant Target entity description: Steven Grant is an American comic book writer best known for creating the graphic novel that inspired the film "2 Guns."
-
A.
Steven Grant
Steven Grant is one of the main identities of the Marvel Comics character Moon Knight, portrayed in the Marvel Cinematic Universe by Oscar Isaac.
-
B.
Arthur Grant
Arthur Grant was a British cinematographer best known for his work on numerous Hammer Films productions in the mid-20th century.
-
C.
Michael Graydon
Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
-
D.
Nick Grindé
Nick Grindé was a screenwriter active during early Hollywood cinema, known for contributing to films such as the 1930 drama "The Divorcee."
-
E.
Jonathan Scott
Jonathan Scott is a wildlife photographer and television presenter best known for his work on BBC nature documentaries, particularly those focusing on big cats in Africa.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf28df081908d897d7b9ec7939d |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce865ab4819088221189344b3801 |
completed | May 3, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69f9fd5b82f48190b0b89ddca25883cc |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f9fea0a9dc8190b5b65dfec9626949 |
completed | May 5, 2026, 2:28 p.m. |
Created at: April 9, 2026, 10:17 p.m.