Triple
T5436288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javan rhinoceros |
E122014
|
entity |
| Predicate | skinDescription |
P8035
|
FINISHED |
| Object | thick gray-brown skin with folds |
—
|
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 gray-brown skin with folds | Statement: [Javan rhinoceros, skinDescription, thick gray-brown skin with folds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinDescription Context triple: [Javan rhinoceros, skinDescription, thick gray-brown skin with folds]
-
A.
skinCharacteristic
chosen
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
B.
surfaceDescription
Indicates that one entity provides a textual or qualitative description of the surface characteristics or appearance of another entity.
-
C.
skinThickness
Indicates the measured thickness of an entity’s skin, typically quantifying how thick its outer tissue layer is.
-
D.
skinSecretionFunction
Indicates the function or role served by a substance secreted through the skin in the context of an organism’s biology or behavior.
-
E.
fleshColor
Indicates the color or hue of an entity’s flesh or skin.
- 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.