Triple
T28956512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bignoniaceae |
E731177
|
entity |
| Predicate | staminodePresence |
P166061
|
FINISHED |
| Object | often 1 staminode |
—
|
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: often 1 staminode | Statement: [Bignoniaceae, staminodePresence, often 1 staminode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: staminodePresence Context triple: [Bignoniaceae, staminodePresence, often 1 staminode]
-
A.
statePresence
Indicates that an entity exists, operates, or is present within a particular state or governmental jurisdiction.
-
B.
tendrilPresence
Indicates that an entity possesses or exhibits tendrils, or that tendrils are present in association with it.
-
C.
cortexPresence
Indicates that a cortex is present or exists in relation to the specified entity or structure.
-
D.
hasHumanPresence
Indicates that humans are physically present in or occupying a given location, object, or context.
-
E.
modernPresence
Indicates that something exists, appears, or is active in the contemporary or present-day context.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65bbd8b188190bb8c1a0dbdbbccc6 |
completed | May 2, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65b136b30819090cf59fb772f35f1 |
completed | May 2, 2026, 8:14 p.m. |
Created at: April 28, 2026, 8:47 a.m.