Triple
T22427660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metopium toxiferum |
E554414
|
entity |
| Predicate | leafletCount |
P66970
|
FINISHED |
| Object | 3 to 7 leaflets |
—
|
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: 3 to 7 leaflets | Statement: [Metopium toxiferum, leafletCount, 3 to 7 leaflets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafletCount Context triple: [Metopium toxiferum, leafletCount, 3 to 7 leaflets]
-
A.
numberOfLeaflets
chosen
Indicates the count of individual leaflets associated with or contained within a given entity.
-
B.
tileCount
Indicates the number of tiles associated with or contained by a given entity or area.
-
C.
hasLeaflet
Indicates that one entity includes, is accompanied by, or is associated with a leaflet (such as an insert, flyer, or informational sheet).
-
D.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
-
E.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2f054c819093fbe173c8a4a544 |
completed | April 29, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.