Triple
T30151413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naughty and Nice list |
E766405
|
entity |
| Predicate | linkedToCharacterTrait |
P37384
|
FINISHED |
| Object | kindness |
—
|
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: kindness | Statement: [Naughty and Nice list, linkedToCharacterTrait, kindness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToCharacterTrait Context triple: [Naughty and Nice list, linkedToCharacterTrait, kindness]
-
A.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
B.
associatedWithPersonaTrait
Indicates that an entity is linked to or characterized by a particular persona trait or attribute.
-
C.
hasSupportingCharacterTrait
Indicates that a supporting character possesses a particular trait, quality, or characteristic.
-
D.
linkedToCharacterDevelopmentOf
Indicates a relationship where something contributes to, influences, or is otherwise connected with the character development of an entity.
-
E.
childCharacterTrait
Indicates that a child possesses or exhibits a particular character trait.
- 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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
Created at: April 29, 2026, 7:20 p.m.