Triple
T30906131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinfonie in h-Moll |
E787304
|
entity |
| Predicate | associatedNicknameLanguage |
P40387
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Sinfonie in h-Moll, associatedNicknameLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedNicknameLanguage Context triple: [Sinfonie in h-Moll, associatedNicknameLanguage, English]
-
A.
hasLanguageOfNickname
chosen
Indicates that an entity’s nickname is expressed in, or associated with, a particular language.
-
B.
translationOfNickname
Indicates that one name is a translated form of another name that functions as a nickname.
-
C.
hasNicknames
Indicates that an entity is known or referred to by one or more alternative informal names.
-
D.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
E.
nicknameInPortuguese
Indicates that one entity is used as a nickname for another entity specifically in the Portuguese language.
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:50 p.m.