Triple
T35924292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tetracera volubilis |
E1038975
|
entity |
| Predicate | vernacularUse |
P184232
|
FINISHED |
| Object | ethnobotanical applications |
—
|
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: ethnobotanical applications | Statement: [Tetracera volubilis, vernacularUse, ethnobotanical applications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vernacularUse Context triple: [Tetracera volubilis, vernacularUse, ethnobotanical applications]
-
A.
vernacularOf
Indicates that one language or dialect is the everyday, locally used form corresponding to another, more general or standard language.
-
B.
vernacularGroup
Indicates a relationship where entities are grouped or associated based on sharing the same vernacular (local or commonly spoken) language.
-
C.
typicalLanguageUse
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
D.
linguisticUsage
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
-
E.
territorialUse
Indicates the use, control, or occupation of a geographic area or territory by an entity.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:07 p.m.