Triple
T9340778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Comedian |
E224757
|
entity |
| Predicate | roleInTheme |
P30025
|
FINISHED |
| Object | embodies the dark, deconstructive tone of Watchmen |
—
|
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: embodies the dark, deconstructive tone of Watchmen | Statement: [The Comedian, roleInTheme, embodies the dark, deconstructive tone of Watchmen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTheme Context triple: [The Comedian, roleInTheme, embodies the dark, deconstructive tone of Watchmen]
-
A.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
-
B.
playRoleIn
Indicates that an entity participates in or performs a specific function, character, or part within an event, context, or system.
-
C.
roleInRhyme
Indicates the specific function or part an entity plays within a rhyme, such as a character, object, or structural element of the rhyming text.
-
D.
themeInvolvingCharacter
chosen
Indicates that a theme, motif, or abstract concept centrally involves or is significantly shaped by a particular character.
-
E.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
- 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_69ca84286fcc81909f6e7fd7a7e862a2 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bae2e2481909effc2dc89a642c5 |
completed | April 1, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:40 p.m.