Triple
T34905679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German 2 euro commemorative coin (Schleswig-Holstein, 2006) |
E1006718
|
entity |
| Predicate | obverseTextLanguage |
P15804
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [German 2 euro commemorative coin (Schleswig-Holstein, 2006), obverseTextLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: obverseTextLanguage Context triple: [German 2 euro commemorative coin (Schleswig-Holstein, 2006), obverseTextLanguage, German]
-
A.
languageOfManuscript
Indicates the language in which a given manuscript is written.
-
B.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
-
C.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
D.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
E.
secondaryLanguageOfInscriptions
Indicates that a specified language serves as the secondary language used in the inscriptions associated with a given entity.
- 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.