Triple
T6809866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolcetto |
E156601
|
entity |
| Predicate | skinCharacteristics |
P8035
|
FINISHED |
| Object | thick skins |
—
|
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: thick skins | Statement: [Dolcetto, skinCharacteristics, thick skins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinCharacteristics Context triple: [Dolcetto, skinCharacteristics, thick skins]
-
A.
skinCharacteristic
chosen
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
B.
eyeCharacteristic
Indicates a relationship where an entity possesses a specific attribute, feature, or quality of its eyes.
-
C.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
D.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
E.
fiberCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a fiber or fibrous material.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30c741881909e220b05aa564bc2 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.