Triple
T33661200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Beale |
E862356
|
entity |
| Predicate | perceptionFilteredThrough |
P22974
|
FINISHED |
| Object | child’s point of view |
—
|
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: child’s point of view | Statement: [Mrs. Beale, perceptionFilteredThrough, child’s point of view]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceptionFilteredThrough Context triple: [Mrs. Beale, perceptionFilteredThrough, child’s point of view]
-
A.
influencedPerceptionOf
chosen
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
B.
viewOnPerception
Indicates a relationship where one entity expresses or embodies a particular stance, interpretation, or opinion about the nature or process of perception.
-
C.
typicalPerception
Indicates the usual or most common way an entity is perceived or experienced through the senses.
-
D.
intendedPerception
Indicates that one entity is meant or designed to be perceived (e.g., seen, heard, or otherwise sensed) by another entity.
-
E.
hasPerception
Indicates that one entity is aware of, senses, or recognizes another entity or phenomenon.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:42 a.m.