Triple
T6783278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coco de Mer palm |
E155736
|
entity |
| Predicate | leafSpan |
P72804
|
FINISHED |
| Object | up to about 10 meters across |
—
|
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: up to about 10 meters across | Statement: [Coco de Mer palm, leafSpan, up to about 10 meters across]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafSpan Context triple: [Coco de Mer palm, leafSpan, up to about 10 meters across]
-
A.
leafMargin
Indicates the type or pattern of the edge or border of a leaf (e.g., smooth, serrated, lobed).
-
B.
numberOfSpans
Indicates the total count of distinct spans or segments associated with an entity or within a specified context.
-
C.
archSpan
Indicates the distance or extent between the supports of an arch, typically measured horizontally from one side to the other.
-
D.
leafType
Indicates the specific kind or classification of leaf associated with an entity.
-
E.
isSpanning
Indicates that one entity extends across, covers, or bridges the full width, extent, or duration of another entity.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d289958481908ad4f9467a107083 |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d182213c819086fcbbfd3d64d80b |
completed | March 27, 2026, 6:50 p.m. |
Created at: March 27, 2026, 2:14 p.m.