Triple
T24763515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cosy Moments |
E619515
|
entity |
| Predicate | toneWithinFiction |
P157104
|
FINISHED |
| Object | light-hearted |
—
|
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: light-hearted | Statement: [Cosy Moments, toneWithinFiction, light-hearted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneWithinFiction Context triple: [Cosy Moments, toneWithinFiction, light-hearted]
-
A.
eraWithinFiction
Indicates that a time period or era exists inside the narrative world or timeline of a fictional work.
-
B.
languageWithinFiction
Indicates that a language is used or exists within the context of a fictional work or fictional universe.
-
C.
showWithinFiction
Indicates that one entity is depicted, referenced, or occurs as part of the fictional world or narrative context of another entity.
-
D.
targetAudienceWithinFiction
Indicates that the intended audience of a work exists as characters or entities within the fictional world depicted by that work.
-
E.
guardedByInFiction
Indicates that one fictional entity is protected or watched over by another within a narrative context.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a330f0819081bc60b9275d883d |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f410a001788190a457e41f53aaf90c |
completed | May 1, 2026, 2:32 a.m. |
Created at: April 18, 2026, 4:28 a.m.