Triple
T36566108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merychippus |
E901980
|
entity |
| Predicate | enamelAdaptation |
P128829
|
FINISHED |
| Object | thickened dental enamel for abrasive 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: thickened dental enamel for abrasive grasses | Statement: [Merychippus, enamelAdaptation, thickened dental enamel for abrasive grasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enamelAdaptation Context triple: [Merychippus, enamelAdaptation, thickened dental enamel for abrasive grasses]
-
A.
toothAdaptation
chosen
Indicates how an organism’s teeth are structurally or functionally modified in response to its diet, environment, or evolutionary pressures.
-
B.
coatAdaptation
Indicates that an entity’s coat or outer covering has changed or developed in response to environmental or functional conditions.
-
C.
dentition
Indicates the type, arrangement, or condition of teeth that an entity possesses.
-
D.
distinguishingDentalFeature
Indicates that one entity has a dental characteristic that serves to differentiate it from another entity or group.
-
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_69f76e6416708190a9754b8c52d4e453 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.