Triple
T1604946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange River Trek |
E34479
|
entity |
| Predicate | involvedUseOf |
P25490
|
FINISHED |
| Object | ox-wagons |
—
|
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: ox-wagons | Statement: [Orange River Trek, involvedUseOf, ox-wagons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedUseOf Context triple: [Orange River Trek, involvedUseOf, ox-wagons]
-
A.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
B.
oftenInvolvedWith
Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another entity.
-
C.
involvesIssue
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
-
D.
areUsedIn
chosen
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
formerlyInvolved
Indicates that an entity previously participated in or was associated with another entity or activity, but is no longer involved.
- 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fa6926081908bc78d15c0be3185 |
completed | March 5, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69a907c35f848190a2428c52e81d013e |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.