Triple
T33107314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wittdün auf Amrum |
E847221
|
entity |
| Predicate | hasLocalNameInDanish |
P58114
|
FINISHED |
| Object | Vittdøn |
—
|
NE NERFINISHED |
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: Vittdøn | Statement: [Wittdün auf Amrum, hasLocalNameInDanish, Vittdøn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalNameInDanish Context triple: [Wittdün auf Amrum, hasLocalNameInDanish, Vittdøn]
-
A.
hasNameInDanish
chosen
Indicates that an entity is associated with a specific name expressed in the Danish language.
-
B.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
C.
hasLocalNameInNorthFrisian
Indicates that an entity has a specific local name expressed in the North Frisian language.
-
D.
hasDanishNameMeaning
Indicates that an entity has a Danish name whose semantic meaning or etymology is being specified.
-
E.
hasNameInNorwegian
Indicates that an entity is associated with a specific name expressed in the Norwegian 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_69f3495686508190b76bf20fa5e00bf7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe6739d4dc8190ae7505c089bbac29 |
completed | May 8, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69fe6541dffc81909c66a61ba69f38fc |
completed | May 8, 2026, 10:35 p.m. |
Created at: May 1, 2026, 1:26 a.m.