Triple
T33462076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Rouletabille series |
E856945
|
entity |
| Predicate | characterRoleOfMainCharacter |
P20969
|
FINISHED |
| Object | reporter |
—
|
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: reporter | Statement: [Joseph Rouletabille series, characterRoleOfMainCharacter, reporter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfMainCharacter Context triple: [Joseph Rouletabille series, characterRoleOfMainCharacter, reporter]
-
A.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
B.
characterTitle
Indicates that a character holds or is associated with a specific title, rank, or formal designation.
-
C.
roleForProtagonist
Indicates the specific narrative or functional role that an entity plays in relation to the story’s main protagonist.
-
D.
characterStatusInStory
Indicates the role or condition a character holds within the context of a specific story or narrative.
-
E.
protagonistType
chosen
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff370698ec81909bb1596d7d4112ba |
completed | May 9, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69ff3699b6288190b564839cb05f5cf6 |
completed | May 9, 2026, 1:28 p.m. |
Created at: May 1, 2026, 1:37 a.m.