Triple
T27929035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Marcia Fieldstone |
E707924
|
entity |
| Predicate | storyRoleType |
P42552
|
FINISHED |
| Object | supporting character |
—
|
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: supporting character | Statement: [Dr. Marcia Fieldstone, storyRoleType, supporting character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyRoleType Context triple: [Dr. Marcia Fieldstone, storyRoleType, supporting character]
-
A.
roleInStories
chosen
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
B.
genreRole
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
-
C.
stagePersonaOf
Indicates a relationship where one entity is the staged or performed persona, role, or character representation of another entity.
-
D.
themeRole
Indicates that an entity is the primary participant undergoing or affected by the action or event expressed by a predicate.
-
E.
storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
- 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 7:01 p.m.