Triple
T2993285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angora cats |
E81005
|
entity |
| Predicate | furCharacteristic |
P40326
|
FINISHED |
| Object | single coat |
—
|
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: single coat | Statement: [Angora cats, furCharacteristic, single coat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: furCharacteristic Context triple: [Angora cats, furCharacteristic, single coat]
-
A.
fiberCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a fiber or fibrous material.
-
B.
faunaCharacteristic
Indicates that an entity has a specific trait, feature, or quality related to animals or animal life.
-
C.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
D.
flowerCharacteristic
Indicates that a flower possesses a particular attribute, quality, or feature (such as color, shape, size, or scent).
-
E.
biologicalCharacteristic
chosen
Indicates that one entity possesses or exhibits a particular biological trait, feature, or property in relation to another.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99e12c5c8190af7cc20e4c48bf45 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad961403108190bbecb8d3608fd4e0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.