Triple
T3347744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bennett’s tree-kangaroo |
E70414
|
entity |
| Predicate | limbAdaptation |
P2375
|
FINISHED |
| Object | strong forelimbs for climbing |
—
|
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: strong forelimbs for climbing | Statement: [Bennett’s tree-kangaroo, limbAdaptation, strong forelimbs for climbing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: limbAdaptation Context triple: [Bennett’s tree-kangaroo, limbAdaptation, strong forelimbs for climbing]
-
A.
limbMorphology
Indicates the structural form, shape, and configuration of an organism’s limbs in relation to its body.
-
B.
limbType
Indicates the specific kind or category of limb associated with an entity (e.g., arm, leg, wing, fin).
-
C.
hasLimbs
Indicates that an entity possesses one or more limbs as physical appendages.
-
D.
beakShapeAdaptedTo
Indicates that an organism’s beak shape is specifically suited or modified to function effectively in a particular environment, diet, or ecological role.
-
E.
adaptationType
chosen
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb21c64448190a29631ea8f029868 |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42df1d48190874bb05f95deefde |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.