Triple
T1074956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton-on-Thames |
E23814
|
entity |
| Predicate | hasPrimaryRiverFeature |
P14635
|
FINISHED |
| Object | Thames riverside |
—
|
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: Thames riverside | Statement: [Walton-on-Thames, hasPrimaryRiverFeature, Thames riverside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryRiverFeature Context triple: [Walton-on-Thames, hasPrimaryRiverFeature, Thames riverside]
-
A.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
B.
hasMajorTownOnRiver
Indicates that a major town is located on and directly associated with a particular river.
-
C.
riverFeatureType
chosen
Indicates the specific kind or category of physical or functional feature associated with a river (e.g., source, mouth, tributary, channel segment).
-
D.
hasMajorCityOnRiver
Indicates that a major city is located on and directly associated with a particular river.
-
E.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92e480c81909a848b48c196a293 |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.