Triple
T6488635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | southern white rhinoceros |
E147977
|
entity |
| Predicate | frontHornLength |
P71016
|
FINISHED |
| Object | up to about 1.5 meters |
—
|
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: up to about 1.5 meters | Statement: [southern white rhinoceros, frontHornLength, up to about 1.5 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontHornLength Context triple: [southern white rhinoceros, frontHornLength, up to about 1.5 meters]
-
A.
frontLength
Indicates the length measurement of the front side or edge of an object relative to its overall dimensions.
-
B.
frontEnginePosition
Indicates that the engine of a vehicle is located at the front portion of the vehicle.
-
C.
hasHornMaterial
Indicates that an entity’s horn is made of, or composed from, a specified material.
-
D.
hasFrontFeature
Indicates that an entity possesses a specific characteristic, component, or attribute located on its front side.
-
E.
hasFront
Indicates that an entity possesses or is associated with a front-facing side, surface, or portion.
- F. None of above. chosen
Provenance (4 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a97fff88190b6f993c14df62649 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067f1ef148190bc0355abe83f7e16 |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:52 p.m.