Triple
T29026072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Träumerei |
E737594
|
entity |
| Predicate | hasMoodMarking |
P190342
|
FINISHED |
| Object | zart und mit Ausdruck (tender and with expression) |
—
|
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: zart und mit Ausdruck (tender and with expression) | Statement: [Träumerei, hasMoodMarking, zart und mit Ausdruck (tender and with expression)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoodMarking Context triple: [Träumerei, hasMoodMarking, zart und mit Ausdruck (tender and with expression)]
-
A.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
B.
hasCaseMarking
Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
-
C.
hasMoodDistinctions
Indicates that something differentiates or categorizes entities based on their moods or emotional states.
-
D.
hasPersonMarkingOnVerb
Indicates that the verb carries explicit grammatical marking that identifies or agrees with the person (e.g., first, second, third person) of its subject or argument.
-
E.
hasMoodCategory
Indicates that an entity is associated with a particular mood classification or emotional category.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc4b5f22c8190b8b256adbdc2570c |
completed | May 7, 2026, 4:58 p.m. |
Created at: April 28, 2026, 9:52 a.m.