Triple
T25194032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophia Peletier |
E630953
|
entity |
| Predicate | storyRoleInTV |
P42552
|
FINISHED |
| Object | catalyst for Carol Peletier's character development |
—
|
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: catalyst for Carol Peletier's character development | Statement: [Sophia Peletier, storyRoleInTV, catalyst for Carol Peletier's character development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyRoleInTV Context triple: [Sophia Peletier, storyRoleInTV, catalyst for Carol Peletier's character development]
-
A.
narrativeRoleInSeries
Indicates the specific narrative function or role an entity plays within a particular series or serialized work.
-
B.
roleInStories
chosen
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
C.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
D.
storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
-
E.
roleOfCharacter
Indicates that one entity serves as the narrative or functional role played by a character within a story, scenario, or context.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f46e1206f88190bfacdc420027c354 |
completed | May 1, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69f4683472ec8190a483b3b8afe71720 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 12:45 p.m.