Triple
T29027250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Am leuchtenden Sommermorgen |
E737626
|
entity |
| Predicate | hasPoeticImagery |
P182632
|
FINISHED |
| Object | summer morning |
—
|
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: summer morning | Statement: [Am leuchtenden Sommermorgen, hasPoeticImagery, summer morning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoeticImagery Context triple: [Am leuchtenden Sommermorgen, hasPoeticImagery, summer morning]
-
A.
poeticDepiction
chosen
Indicates that one entity artistically represents or describes another using poetic or figurative language.
-
B.
hasPoeticLyrics
Indicates that something (such as a song, text, or speech) contains lyrics or wording that are artistic, expressive, or characteristic of poetry.
-
C.
hasSpiritualImagery
Indicates that something contains or employs imagery related to spiritual, religious, or transcendent themes.
-
D.
hasPoeticDevice
Indicates that one entity (typically a text or passage) employs or contains a specific poetic device present in the other entity.
-
E.
usesPoeticSources
Indicates that one entity draws upon or incorporates poetic works or poetic material as sources in relation to another entity or context.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: April 28, 2026, 9:53 a.m.