Triple
T22721908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | vicuña |
E561883
|
entity |
| Predicate | woolCharacteristic |
P35372
|
FINISHED |
| Object | exceptionally fine |
—
|
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: exceptionally fine | Statement: [vicuña, woolCharacteristic, exceptionally fine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: woolCharacteristic Context triple: [vicuña, woolCharacteristic, exceptionally fine]
-
A.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
-
B.
fiberCharacteristic
chosen
Indicates a relationship where a specific characteristic or property is attributed to a fiber or fibrous material.
-
C.
textileFeature
Indicates a characteristic, property, or notable aspect associated with a textile or fabric.
-
D.
fiberwiseDescription
Indicates a description or characterization that is given separately for each fiber in a fibered or parameterized structure, specifying how the relationship or action behaves over individual fibers.
-
E.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
- 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17926ae0c8190af8493cab6b15261 |
completed | April 29, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69eed2a971c0819088af574e40c9343f |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:20 p.m.