Triple
T842693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glyptostrobus |
E18210
|
entity |
| Predicate | rootCharacteristic |
P662
|
FINISHED |
| Object | adapted to waterlogged soils |
—
|
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: adapted to waterlogged soils | Statement: [Glyptostrobus, rootCharacteristic, adapted to waterlogged soils]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rootCharacteristic Context triple: [Glyptostrobus, rootCharacteristic, adapted to waterlogged soils]
-
A.
rootStructure
Indicates that one entity serves as the primary or foundational structural element upon which another entity is based or organized.
-
B.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
typicalLeafCharacteristic
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
D.
mobilityCharacteristic
Indicates a relationship where an entity is described or classified in terms of its movement or transportation-related properties, such as how, how well, or under what conditions it can move or be moved.
-
E.
fruitCharacteristic
Indicates that a specified characteristic or property is attributed to a particular fruit.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe8a0bc81909b54af465e67be1f |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7f396c8190aa8b8dfbe0b4f732 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.