Triple
T2643457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wild Wood |
E62928
|
entity |
| Predicate | moodShiftFromPreviousChapter |
P41006
|
FINISHED |
| Object | from cozy and pastoral to tense and ominous |
—
|
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: from cozy and pastoral to tense and ominous | Statement: [The Wild Wood, moodShiftFromPreviousChapter, from cozy and pastoral to tense and ominous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moodShiftFromPreviousChapter Context triple: [The Wild Wood, moodShiftFromPreviousChapter, from cozy and pastoral to tense and ominous]
-
A.
narrativeShift
Indicates a change in the narrative perspective, time, focus, or structure within a story or discourse.
-
B.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
C.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
D.
protagonistStatusBeforeSleep
Indicates the role or condition the protagonist is in immediately prior to going to sleep.
-
E.
characterArc
Indicates the developmental journey or transformation a character undergoes over the course of a narrative.
- F. None of above. chosen
Provenance (4 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd90046dc81908bab3440733f1e98 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd879bb808190bd2c34de1664c816 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:53 p.m.