Triple
T139498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinophyta |
E2819
|
entity |
| Predicate | needleAdaptation |
P2375
|
FINISHED |
| Object | reduced surface area to limit water loss |
—
|
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: reduced surface area to limit water loss | Statement: [Pinophyta, needleAdaptation, reduced surface area to limit water loss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: needleAdaptation Context triple: [Pinophyta, needleAdaptation, reduced surface area to limit water loss]
-
A.
adaptationType
chosen
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
B.
adaptation
Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
-
C.
fireAdaptation
Indicates that an entity possesses traits or mechanisms that enable it to survive, reproduce, or otherwise benefit in environments where fire occurs.
-
D.
adaptedTo
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
E.
updated
Indicates that an entity has been modified or brought to a more recent state compared to its previous version or status.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c679d88190bc71775dab2cfc64 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.