Triple
T32902058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schiffbruch mit Zuschauer |
E841637
|
entity |
| Predicate | hasMetaphorType |
P197807
|
FINISHED |
| Object | nautical metaphor |
—
|
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: nautical metaphor | Statement: [Schiffbruch mit Zuschauer, hasMetaphorType, nautical metaphor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetaphorType Context triple: [Schiffbruch mit Zuschauer, hasMetaphorType, nautical metaphor]
-
A.
hasMetaphoricalForm
Indicates that one entity is expressed, represented, or understood through a metaphorical form or figurative expression involving another entity.
-
B.
hasMetaphoricalSubject
Indicates that one entity functions as the metaphorical subject or source domain in a figurative or metaphorical expression involving another entity.
-
C.
hasMetaphoricalContent
Indicates that something contains or expresses meaning through metaphorical, rather than purely literal, content.
-
D.
hasMetapattern
Indicates that one entity is associated with, characterized by, or governed by a higher-level structural pattern or schema represented by another entity.
-
E.
keyMetaphor
Indicates that one entity functions as a central or primary metaphor used to conceptualize, explain, or structure understanding of another entity.
- 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_69f34946a5208190bbd79f0fec4323bd |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69feabcda59481908f2bc13b46fcced1 |
completed | May 9, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69feaabd63f88190b30dcf6dd2ea39d1 |
completed | May 9, 2026, 3:32 a.m. |
| PDg | Predicate description generation | batch_69feabcca6148190a8eb7b6fa33729c7 |
completed | May 9, 2026, 3:36 a.m. |
Created at: May 1, 2026, 1:19 a.m.