Triple
T2238344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyathea |
E49334
|
entity |
| Predicate | hasVernacularName |
P21937
|
FINISHED |
| Object | silver fern (for Cyathea dealbata) |
—
|
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: silver fern (for Cyathea dealbata) | Statement: [Cyathea, hasVernacularName, silver fern (for Cyathea dealbata)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVernacularName Context triple: [Cyathea, hasVernacularName, silver fern (for Cyathea dealbata)]
-
A.
hasNameInLocalLanguage
chosen
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
B.
hasGlottologName
Indicates that an entity is associated with a specific name as recorded in the Glottolog linguistic database.
-
C.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
D.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
E.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc096c7748190a545cc9b229bde62 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.