Triple
T1298892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalgety Bay |
E27715
|
entity |
| Predicate | hasEnvironmentalIssueHistory |
P1006
|
FINISHED |
| Object | radium contamination |
—
|
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: radium contamination | Statement: [Dalgety Bay, hasEnvironmentalIssueHistory, radium contamination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnvironmentalIssueHistory Context triple: [Dalgety Bay, hasEnvironmentalIssueHistory, radium contamination]
-
A.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
B.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
-
C.
environmentalIssue
chosen
Indicates that something is a problem or concern related to the natural environment, such as harm, risk, or negative impact on ecosystems or resources.
-
D.
hasFireHistory
Indicates that an entity has experienced one or more fire events in the past.
-
E.
historicallyPollutedBy
Indicates that an entity has experienced pollution in the past as a result of actions or emissions from another entity.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.