Triple
T1287441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | northern white rhinoceros |
E27466
|
entity |
| Predicate | mainPoachingDriver |
P28093
|
FINISHED |
| Object | demand for rhino horn |
—
|
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: demand for rhino horn | Statement: [northern white rhinoceros, mainPoachingDriver, demand for rhino horn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPoachingDriver Context triple: [northern white rhinoceros, mainPoachingDriver, demand for rhino horn]
-
A.
mainSingle
Indicates that an entity is the primary or sole main instance among a set of related entities.
-
B.
mainFunctions
Indicates that the subject serves as the primary or central functional component or role for the object.
-
C.
preysOn
Indicates that one entity hunts, kills, and consumes another entity as a food source.
-
D.
mainLine
Indicates that something serves as the primary or central line, route, or sequence among a set of related lines.
-
E.
shootsCatches
Indicates that one entity shoots something that is then caught by another entity.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d1a5508190b4461df77f560df4 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfa205ec81909d8170b398345615 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:51 p.m.