Triple
T38160212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spalding, Lincolnshire |
E952994
|
entity |
| Predicate | localRiverFeature |
P14635
|
FINISHED |
| Object | drainage channels and fens |
—
|
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: drainage channels and fens | Statement: [Spalding, Lincolnshire, localRiverFeature, drainage channels and fens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localRiverFeature Context triple: [Spalding, Lincolnshire, localRiverFeature, drainage channels and fens]
-
A.
watercourseFeature
Indicates that a feature is a physical characteristic or component associated with a watercourse (such as a river, stream, or canal).
-
B.
riverineLocation
Indicates that something is located in, along, or directly associated with a river or river system.
-
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.
raceRiver
Indicates that an entity participates in a race that takes place on or along a river.
-
E.
riverPhenomenon
Indicates a natural event, condition, or process that occurs in or directly affects a river.
- 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_69f76f0b93c48190a117319ab3a9f282 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
Created at: May 3, 2026, 4:21 p.m.