Triple
T3451860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SimCorp |
E72809
|
entity |
| Predicate | languageOfProduct |
P48899
|
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: [SimCorp, languageOfProduct, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfProduct Context triple: [SimCorp, languageOfProduct, English]
-
A.
languageOfMaterial
Indicates the language in which a given material, resource, or content is expressed or presented.
-
B.
presentedInLanguage
Indicates that something (such as content, information, or a work) is expressed or made available using a particular language.
-
C.
languageOfDocumentation
Indicates the language in which the documentation for an entity is written or provided.
-
D.
languageCodeISO639-1
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
-
E.
languageOfInternationalEdition
Indicates that a specified language is the language used in the international edition of a work or publication.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba7465248190947f9096e230e1c4 |
completed | March 8, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69adae0255b48190a9069f7871c7a012 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb1ecb02881908394f197e31431b4 |
completed | March 8, 2026, 5:29 p.m. |
Created at: March 8, 2026, 3:16 p.m.