Triple
T29027012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Im wunderschönen Monat Mai |
E737619
|
entity |
| Predicate | cycleNumberOfSongs |
P10577
|
FINISHED |
| Object | 16 (in Dichterliebe) |
—
|
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: 16 (in Dichterliebe) | Statement: [Im wunderschönen Monat Mai, cycleNumberOfSongs, 16 (in Dichterliebe)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cycleNumberOfSongs Context triple: [Im wunderschönen Monat Mai, cycleNumberOfSongs, 16 (in Dichterliebe)]
-
A.
cycleBy
Indicates that one entity moves or travels by means of riding a bicycle (or similar cycle) in relation to another entity or context.
-
B.
hasSongCycle
Indicates that one entity (typically a musical work or collection) includes or is associated with a specific song cycle as part of its structure or content.
-
C.
numberOfSongs
chosen
Indicates the quantity of songs associated with a given entity.
-
D.
catalogueNumberOfCycle
Indicates that an entity is assigned a specific catalogue number identifying a particular cycle within a cataloging system.
-
E.
cycleWith
Indicates that two or more entities participate together in a cycling activity, such as riding bicycles along the same route or at the same time.
- 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_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 9:53 a.m.