Triple
T36504927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acrocodia |
E899433
|
entity |
| Predicate | digitigradeOrUnguligrade |
P146633
|
FINISHED |
| Object | unguligrade |
—
|
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: unguligrade | Statement: [Acrocodia, digitigradeOrUnguligrade, unguligrade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: digitigradeOrUnguligrade Context triple: [Acrocodia, digitigradeOrUnguligrade, unguligrade]
-
A.
digitigrade
chosen
Indicates that an animal moves or stands with its weight borne primarily on its toes, with the heel elevated off the ground.
-
B.
zygodactylFeetDescription
Indicates that an entity possesses zygodactyl feet, meaning its toes are arranged in two opposing pairs (typically two forward and two backward).
-
C.
hasHoovesOf
Indicates that one entity possesses or is characterized by the hooves belonging to another entity.
-
D.
hasHindLegsOf
Indicates that one entity possesses or is characterized by the hind legs belonging to or derived from another entity.
-
E.
hasTeethAdaptedFor
Indicates that an organism’s teeth are specially shaped or structured to suit a particular function, diet, or environmental condition.
- 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_69f76e5b92088190933afda3f7531dd4 |
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_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:10 p.m.