Triple
T1773098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An meinem Herzen, an meiner Brust |
E38917
|
entity |
| Predicate | hasTitleTranslation |
P2303
|
FINISHED |
| Object | At my heart, at my breast |
—
|
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: At my heart, at my breast | Statement: [An meinem Herzen, an meiner Brust, hasTitleTranslation, At my heart, at my breast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleTranslation Context triple: [An meinem Herzen, an meiner Brust, hasTitleTranslation, At my heart, at my breast]
-
A.
hasTitleInLanguage
Indicates that an entity has a specific title expressed in a particular language.
-
B.
hasTranslation
chosen
Indicates that one entity is a translation or translated version of another entity in a different language.
-
C.
hasTitleInGerman
Indicates that an entity has a specific title or name expressed in the German language.
-
D.
hasLatinTitle
Indicates that an entity possesses a title or name expressed in Latin.
-
E.
hasDutchTitle
Indicates that an entity possesses a title or name expressed in the Dutch 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab39fc2c448190bfaf1ee8d474632a |
completed | March 6, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69aa61cbb1288190a7ba38b61905f578 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.