Triple
T21873013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schindleria praematurus |
E540054
|
entity |
| Predicate | skeletalTrait |
P16043
|
FINISHED |
| Object | poorly ossified skeleton |
—
|
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: poorly ossified skeleton | Statement: [Schindleria praematurus, skeletalTrait, poorly ossified skeleton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skeletalTrait Context triple: [Schindleria praematurus, skeletalTrait, poorly ossified skeleton]
-
A.
skeletonFeature
Indicates that one entity is a structural or anatomical skeletal feature or component of another entity.
-
B.
skeleton
Indicates that one entity serves as the basic structural framework or underlying support for another.
-
C.
skeletonLacks
Indicates that an entity’s skeleton does not possess or is missing a specified bone, feature, or structural component.
-
D.
hasSkeleton
Indicates that an entity possesses a skeleton as part of its bodily structure.
-
E.
skeletonCompleteness
chosen
Indicates the degree to which an entity’s skeleton is present, intact, or fully preserved in relation to its expected complete form.
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f337ab5c8190937a457d348c732b |
completed | April 28, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:01 p.m.