Triple
T36129964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quercus glauca |
E1044987
|
entity |
| Predicate | subgenus |
P184734
|
FINISHED |
| Object | Quercus subg. Cerris |
—
|
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: Quercus subg. Cerris | Statement: [Quercus glauca, subgenus, Quercus subg. Cerris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subgenus Context triple: [Quercus glauca, subgenus, Quercus subg. Cerris]
-
A.
subfamily
Indicates that one taxonomic group is a subfamily within a larger family, representing an intermediate rank in biological classification.
-
B.
suborder
Indicates that one entity is a more specific, subordinate ordering or arrangement within the broader ordering defined by another entity.
-
C.
subfamilyCommonName
Indicates that a subfamily is associated with a particular commonly used name.
-
D.
subkingdom
Indicates that one entity is a biological subkingdom, representing a major subordinate division within the broader kingdom-level classification of another entity.
-
E.
subgenre
Indicates that one genre is a more specific, subordinate category within a broader parent genre.
- 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_69f76e356c908190abc6ca1e6a05b011 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b3e0f1c88190985feab6cee8b05e |
completed | May 3, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:08 p.m.