Triple
T20651978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Chapman |
E507516
|
entity |
| Predicate | hasPerspectiveShownThrough |
P8789
|
FINISHED |
| Object | Mark Corrigan’s internal monologue |
—
|
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: Mark Corrigan’s internal monologue | Statement: [Sophie Chapman, hasPerspectiveShownThrough, Mark Corrigan’s internal monologue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerspectiveShownThrough Context triple: [Sophie Chapman, hasPerspectiveShownThrough, Mark Corrigan’s internal monologue]
-
A.
hasPerspectiveEffect
Indicates that one entity visually appears altered in size, shape, or position relative to another due to perspective or viewpoint.
-
B.
hasViewThrough
Indicates that one entity can be seen or visually perceived through another entity acting as an intermediate medium or opening.
-
C.
perspectiveOf
chosen
Indicates that something is expressed, depicted, or understood from the viewpoint or standpoint of a particular entity.
-
D.
hasViewingPointFor
Indicates that one entity serves as a vantage point or location from which another entity can be viewed or observed.
-
E.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af22d6bc8190b9d6877aba5704eb |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.