Triple
T388213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accipitriformes |
E8822
|
entity |
| Predicate | footType |
P12848
|
FINISHED |
| Object | raptorial feet with sharp talons |
—
|
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: raptorial feet with sharp talons | Statement: [Accipitriformes, footType, raptorial feet with sharp talons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: footType Context triple: [Accipitriformes, footType, raptorial feet with sharp talons]
-
A.
heightApproximateFeet
Indicates that one entity’s height is approximately equal to a specified value measured in feet.
-
B.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
C.
preferredFoot
Indicates which foot an entity predominantly uses or favors, especially for actions like kicking or stepping.
-
D.
hasSettlementAtFoot
Indicates that a settlement is located at the base or lower slopes of a geographic feature such as a hill or mountain.
-
E.
heightInInches
Indicates that one entity has a specific height measured in inches.
- F. None of above. chosen
Provenance (4 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5988708190aa86d9460cecf050 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ebac09408190be802b96bb203d5f |
completed | Feb. 28, 2026, 1:20 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.