Triple
T9166713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbian Wyandotte |
E219977
|
entity |
| Predicate | wingFeatherColor |
P84074
|
FINISHED |
| Object | white with some black markings |
—
|
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: white with some black markings | Statement: [Columbian Wyandotte, wingFeatherColor, white with some black markings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wingFeatherColor Context triple: [Columbian Wyandotte, wingFeatherColor, white with some black markings]
-
A.
birdColor
chosen
Indicates the color attribute or hue associated with a bird.
-
B.
plumageFeature
Indicates a relationship where a specific characteristic or attribute is associated with an entity’s plumage (feathers).
-
C.
plumageColorCommon
Indicates that two entities share the same typical or most frequently observed plumage color.
-
D.
plumageColorSource
Indicates the relationship by which the color of an entity’s plumage is derived from or attributed to a particular source.
-
E.
numberOfFeathers
Indicates the specific count of feathers associated with an entity.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaade47cc81909b5c127dc8aa1340 |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc6605c6808190a30d92da006206ac |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:22 p.m.