Triple
T24413043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sivas Kangal dog |
E615504
|
entity |
| Predicate | coatDensity |
P130843
|
FINISHED |
| Object | dense |
—
|
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: dense | Statement: [Sivas Kangal dog, coatDensity, dense]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coatDensity Context triple: [Sivas Kangal dog, coatDensity, dense]
-
A.
furDensity
chosen
Indicates the thickness or concentration of fur covering an entity’s body or a specific body part.
-
B.
beddingCharacteristic
Indicates a relationship where a bedding item is associated with a specific property, feature, or quality it possesses.
-
C.
fiberCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a fiber or fibrous material.
-
D.
carpetKnotDensity
Indicates the number of knots per unit area in a carpet, reflecting how densely the carpet is knotted.
-
E.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
- 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_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2958302ec8190bf32409a5ca00ebf |
completed | April 29, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:11 a.m.