Triple
T22968754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sigillaria |
E571121
|
entity |
| Predicate | leafAttachment |
P107029
|
FINISHED |
| Object | leaves attached directly to stem |
—
|
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: leaves attached directly to stem | Statement: [Sigillaria, leafAttachment, leaves attached directly to stem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafAttachment Context triple: [Sigillaria, leafAttachment, leaves attached directly to stem]
-
A.
leafType
Indicates the specific kind or classification of leaf associated with an entity.
-
B.
leafProperty
Indicates that the subject has a property that is terminal (i.e., not further decomposed into sub-properties) within a property hierarchy or structure.
-
C.
leafPresence
Indicates whether leaves are present on an entity (such as a plant or tree) during a given time or condition.
-
D.
leafPosition
chosen
Indicates the spatial or structural placement of a leaf relative to its supporting plant organ or axis.
-
E.
leafShape
Indicates the characteristic form or outline of a leaf that an entity possesses or exhibits.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182301f388190bb39e3d5b356dc65 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:48 p.m.