Triple
T18915706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walbrook, City of London |
E462718
|
entity |
| Predicate | watercourseHistory |
P133771
|
FINISHED |
| Object | site of culverted River Walbrook |
—
|
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: site of culverted River Walbrook | Statement: [Walbrook, City of London, watercourseHistory, site of culverted River Walbrook]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: watercourseHistory Context triple: [Walbrook, City of London, watercourseHistory, site of culverted River Walbrook]
-
A.
waterSourceHistoric
Indicates that one entity has historically served as a source or supply of water for the other.
-
B.
watercourseFor
Indicates that one entity serves as the watercourse (such as a river or channel) associated with, carrying, or draining another entity.
-
C.
watercourseProgression
Indicates the downstream sequence in which a watercourse flows into other water bodies or watercourses.
-
D.
watercourseName
Indicates the name assigned to a river, stream, or other flowing body of water in the relationship.
-
E.
watercourseFeature
Indicates that a feature is a physical characteristic or component associated with a watercourse (such as a river, stream, or canal).
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c62685408190b17280147e1c247a |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:58 a.m.