Triple
T10213702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginkgoales |
E242390
|
entity |
| Predicate | seedCoatCharacteristic |
P92758
|
FINISHED |
| Object | fleshy outer layer |
—
|
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: fleshy outer layer | Statement: [Ginkgoales, seedCoatCharacteristic, fleshy outer layer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seedCoatCharacteristic Context triple: [Ginkgoales, seedCoatCharacteristic, fleshy outer layer]
-
A.
seedCoatColor
Indicates the color characteristic of the outer protective covering (seed coat) of a seed.
-
B.
seedEnclosure
Indicates that one entity serves as a container or protective space in which another entity’s seeds are held or stored.
-
C.
agronomicTrait
Indicates a relationship where a trait is characterized specifically in terms of its relevance to agricultural growth, management, or productivity of plants or crops.
-
D.
seedDescription
Indicates that a seed has an associated textual description or explanation.
-
E.
seedCommonName
Indicates the commonly used name assigned to a seed in everyday or non-scientific contexts.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa24efc081909714d98943543283 |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
| PDg | Predicate description generation | batch_69d3aa208c248190a0fb186b106389f3 |
completed | April 6, 2026, 12:42 p.m. |
Created at: April 6, 2026, 11:03 a.m.