Triple
T9271475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julian Kirrin |
E222837
|
entity |
| Predicate | typicalRoleInPlot |
P42552
|
FINISHED |
| Object | planner of the group’s actions |
—
|
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: planner of the group’s actions | Statement: [Julian Kirrin, typicalRoleInPlot, planner of the group’s actions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRoleInPlot Context triple: [Julian Kirrin, typicalRoleInPlot, planner of the group’s actions]
-
A.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
B.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
-
C.
roleInStories
chosen
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
D.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
E.
narrativeRoleInSeries
Indicates the specific narrative function or role an entity plays within a particular series or serialized work.
- 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_69ca841ffe208190aa7bcffbef2f8379 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd07865790819099b3865a25dae58a |
completed | April 1, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:33 p.m.