Triple
T21509631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mtsvane |
E530681
|
entity |
| Predicate | skinContactPotential |
P135481
|
FINISHED |
| Object | used for amber (orange) wines |
—
|
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: used for amber (orange) wines | Statement: [Mtsvane, skinContactPotential, used for amber (orange) wines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinContactPotential Context triple: [Mtsvane, skinContactPotential, used for amber (orange) wines]
-
A.
skinContactSuitability
chosen
Indicates that one entity is suitable, safe, or appropriate for direct contact with the skin of another entity.
-
B.
surfaceAccess
Indicates that one entity provides a means for another entity to reach, enter, or interact with a surface or outer layer.
-
C.
routeOfExposure
Indicates the pathway or method by which an agent, substance, or factor comes into contact with or enters an organism or system.
-
D.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
E.
LD50DermalHumanEstimate
Indicates the estimated dermal (skin exposure) dose of a substance that is lethal to 50% of a human population under specified conditions.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:25 p.m.