Triple
T21360063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandy Kessler |
E526748
|
entity |
| Predicate | initialCharacterState |
P89191
|
FINISHED |
| Object | self-absorbed and materialistic |
—
|
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: self-absorbed and materialistic | Statement: [Sandy Kessler, initialCharacterState, self-absorbed and materialistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialCharacterState Context triple: [Sandy Kessler, initialCharacterState, self-absorbed and materialistic]
-
A.
initialCharacterization
Indicates the first or earliest formal description, assessment, or classification made about an entity or situation.
-
B.
initialStatus
chosen
Indicates the original or starting state assigned to an entity before any changes or updates occur.
-
C.
definesStateCharacter
Indicates that something specifies or determines the essential qualities or characteristics of a state or condition.
-
D.
firstCharacterType
Indicates that the type or category of the first character in a sequence or string has a specified value.
-
E.
firstCharacterRules
Indicates that the entity associated with the first character in a sequence has authority, control, or priority over the others.
- 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5bad6a308190a9665734a0fb5f55 |
completed | April 26, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:07 p.m.