Triple
T8950779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dark Tower: The Gunslinger |
E213340
|
entity |
| Predicate | characterRoleOfRolandDeschain |
P23263
|
FINISHED |
| Object | gunslinger |
—
|
LITERAL FINISHED |
How this triple was built (2 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: gunslinger | Statement: [The Dark Tower: The Gunslinger, characterRoleOfRolandDeschain, gunslinger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfRolandDeschain Context triple: [The Dark Tower: The Gunslinger, characterRoleOfRolandDeschain, gunslinger]
-
A.
featuresCharacterRole
chosen
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
B.
roleInBladeII
Indicates that an entity has a specific role or participation in the movie "Blade II."
-
C.
roleInTauris
Indicates that an entity has a specific role or function within the context of Tauris (e.g., a work, setting, or domain associated with Tauris).
-
D.
characterRoleOfGriffin
Indicates that an entity has the character role of a griffin within a given context, such as a story, game, or artwork.
-
E.
GameOfThronesRole
Indicates that one entity plays, voices, or otherwise portrays a character in the television series "Game of Thrones" in relation to another entity.
- F. None of above.
Provenance (3 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670c7244819084978922a9835bc9 |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:59 p.m.