Triple
T5436284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javan rhinoceros |
E122014
|
entity |
| Predicate | hornMaterial |
P618
|
FINISHED |
| Object | keratin |
—
|
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: keratin | Statement: [Javan rhinoceros, hornMaterial, keratin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hornMaterial Context triple: [Javan rhinoceros, hornMaterial, keratin]
-
A.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
material
chosen
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
C.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
-
D.
materialFormedIn
Indicates that a material is created, produced, or formed within a specified process, environment, or context.
-
E.
exampleMaterial
Indicates that something serves as a representative or illustrative material or sample of something else.
- 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.