Triple
T4940933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burton upon Trent |
E110929
|
entity |
| Predicate | waterCharacteristics |
P58792
|
FINISHED |
| Object | high in dissolved minerals |
—
|
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: high in dissolved minerals | Statement: [Burton upon Trent, waterCharacteristics, high in dissolved minerals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterCharacteristics Context triple: [Burton upon Trent, waterCharacteristics, high in dissolved minerals]
-
A.
hasWaterBodyCharacteristic
chosen
Indicates that a water body possesses a specified physical, chemical, or ecological characteristic.
-
B.
hydrologicalCharacteristic
Indicates a relationship where a hydrological feature or condition (such as water flow, level, or behavior) characterizes or describes another entity.
-
C.
waterCondition
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
D.
waterFeature
Indicates the presence of a natural or artificial body or flow of water associated with the subject.
-
E.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd708ba9888190baf4e79c8f159e9f |
completed | March 20, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.