Triple
T6299486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meliaceae |
E141215
|
entity |
| Predicate | hasVernacularGrouping |
P32163
|
FINISHED |
| Object | mahoganies |
—
|
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: mahoganies | Statement: [Meliaceae, hasVernacularGrouping, mahoganies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVernacularGrouping Context triple: [Meliaceae, hasVernacularGrouping, mahoganies]
-
A.
vernacularGrouping
chosen
Indicates a relationship where entities are grouped together based on a shared vernacular, such as common local language, dialect, or colloquial naming.
-
B.
hasLanguageGroup
Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
-
C.
macrolanguageGrouping
Indicates that one language is classified as part of a broader macrolanguage grouping that encompasses multiple closely related language varieties.
-
D.
hasMajorDialectGroup
Indicates that an entity (typically a language) is associated with a primary or major dialect group to which it belongs.
-
E.
hasLinguisticCode
Indicates that an entity is associated with a specific linguistic identifier or code (such as a language or script code) that characterizes its linguistic properties.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645a7e048190af7a609fc74b876a |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:27 p.m.