Triple
T29027123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Im Rhein, im heiligen Strome |
E737622
|
entity |
| Predicate | literaryFormOfText |
P6480
|
FINISHED |
| Object | poem |
—
|
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: poem | Statement: [Im Rhein, im heiligen Strome, literaryFormOfText, poem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryFormOfText Context triple: [Im Rhein, im heiligen Strome, literaryFormOfText, poem]
-
A.
hasLiteraryForm
chosen
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
B.
literaryScript
Indicates a relationship where an entity serves as the written text or script of a literary work, such as a play, film, or other narrative production.
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
literatureType
Indicates the specific category or genre of literature that characterizes or classifies a given work or text.
-
E.
literaryUnit
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
- 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_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 28, 2026, 9:53 a.m.