Triple
T29028361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bunte Blätter, Op. 99, No. 4 |
E737656
|
entity |
| Predicate | collectionTitleTranslation |
P58041
|
FINISHED |
| Object |
Coloured Leaves
Coloured Leaves is the English title of "Bunte Blätter," Op. 99, No. 4, a piano piece by Robert Schumann.
|
E1844514
|
NE FINISHED |
How this triple was built (3 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: Coloured Leaves | Statement: [Bunte Blätter, Op. 99, No. 4, collectionTitleTranslation, Coloured Leaves]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Coloured Leaves Triple: [Bunte Blätter, Op. 99, No. 4, collectionTitleTranslation, Coloured Leaves]
Generated description
Coloured Leaves is the English title of "Bunte Blätter," Op. 99, No. 4, a piano piece by Robert Schumann.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectionTitleTranslation Context triple: [Bunte Blätter, Op. 99, No. 4, collectionTitleTranslation, Coloured Leaves]
-
A.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
-
B.
translationTitle
chosen
Indicates that one entity is the title assigned to a translated version of another entity (such as a work, document, or text).
-
C.
titleInLocalLanguage
Indicates that an entity’s title is expressed in the primary or native language of a specified place or community.
-
D.
languageOfCatalogueTitle
Indicates the language in which a catalogue’s title is expressed.
-
E.
cultTitleLanguage
Indicates the language in which a cult title or religious honorific is expressed.
- F. None of above.
Provenance (6 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_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2505d58bf48190823f8b06939e92c3 |
completed | June 7, 2026, 5:47 a.m. |
| NEDg | Description generation | batch_6a250a085b9481909bfbe976439f91e9 |
completed | June 7, 2026, 6:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a250e23dd70819082500df27b31e03c |
completed | June 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: April 28, 2026, 9:54 a.m.