Triple
T11568605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pymmes Brook |
E274320
|
entity |
| Predicate | hasPollutionIssues |
P98276
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pymmes Brook, hasPollutionIssues, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPollutionIssues Context triple: [Pymmes Brook, hasPollutionIssues, yes]
-
A.
hasPollutionIssue
chosen
Indicates that an entity is affected by, associated with, or characterized by a pollution-related problem or concern.
-
B.
targetPollutant
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
C.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
-
D.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
E.
hasUrbanIssue
Indicates that an entity experiences, is affected by, or is associated with a specific problem or challenge related to urban environments or city life.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd543a48190b834abd8e8ae7b65 |
completed | April 10, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69d85dc3fc2c8190bed7e2111301a77c |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:37 p.m.