Triple
T22520352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theropithecus oswaldi |
E556755
|
entity |
| Predicate | dentitionAdaptation |
P128829
|
FINISHED |
| Object | grazing and tough grasses |
—
|
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: grazing and tough grasses | Statement: [Theropithecus oswaldi, dentitionAdaptation, grazing and tough grasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dentitionAdaptation Context triple: [Theropithecus oswaldi, dentitionAdaptation, grazing and tough grasses]
-
A.
dentition
Indicates the type, arrangement, or condition of teeth that an entity possesses.
-
B.
toothAdaptation
chosen
Indicates how an organism’s teeth are structurally or functionally modified in response to its diet, environment, or evolutionary pressures.
-
C.
distinguishingDentalFeature
Indicates that one entity has a dental characteristic that serves to differentiate it from another entity or group.
-
D.
teethSownBy
Indicates that teeth were deliberately planted or scattered by a particular agent or source.
-
E.
tongueAdaptation
Indicates how an entity’s tongue is structurally or functionally modified to perform specific tasks or suit particular environmental or behavioral demands.
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e31f43c8190899f5e35b150fe85 |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.