Triple
T4635389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Wear |
E101516
|
entity |
| Predicate | hasMeander |
P55931
|
FINISHED |
| Object | Durham peninsula loop |
—
|
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: Durham peninsula loop | Statement: [River Wear, hasMeander, Durham peninsula loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeander Context triple: [River Wear, hasMeander, Durham peninsula loop]
-
A.
hasMeanderingCourse
chosen
Indicates that one entity (typically a path or flow) follows a winding, curving, or indirect route relative to another reference or context.
-
B.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
C.
hasRiverIslands
Indicates that a river contains one or more islands within its course or channel.
-
D.
hasMythicalRiverConfluence
Indicates a relationship where a mythical or legendary river is believed to merge or join with another river or body of water.
-
E.
hasWatercourseType
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a60a66c8190b76f3d3a7da1df55 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.