Triple
T417276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Station railway bridges |
E8020
|
entity |
| Predicate | riverFeatureType |
P14635
|
FINISHED |
| Object | multi-span river crossing |
—
|
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: multi-span river crossing | Statement: [Victoria Station railway bridges, riverFeatureType, multi-span river crossing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riverFeatureType Context triple: [Victoria Station railway bridges, riverFeatureType, multi-span river crossing]
-
A.
riverSystem
Indicates that one entity is a river system to which the other entity belongs or is a component (such as a tributary or segment).
-
B.
waterwaySystem
Indicates that one entity is part of, or belongs to, a connected network of waterways associated with another entity.
-
C.
riverConfluence
Indicates the location or relationship where two or more rivers or streams join and merge into a single watercourse.
-
D.
mouthOfTheWatercourse
Indicates the location where a watercourse ends and flows into a larger body of water.
-
E.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd1ca148190a66bd8c5aad867d5 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb8545c8190a2b8517e7ed5b92e |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.