Triple
T20589373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Passaic River estuary |
E505872
|
entity |
| Predicate | hasPollutionType |
P29039
|
FINISHED |
| Object | polychlorinated biphenyls (PCBs) |
—
|
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: polychlorinated biphenyls (PCBs) | Statement: [Passaic River estuary, hasPollutionType, polychlorinated biphenyls (PCBs)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPollutionType Context triple: [Passaic River estuary, hasPollutionType, polychlorinated biphenyls (PCBs)]
-
A.
hasPollutionIssue
Indicates that an entity is affected by, associated with, or characterized by a pollution-related problem or concern.
-
B.
targetPollutant
chosen
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
C.
hasEnvironmentalImpactType
Indicates that something affects the environment in a specific way categorized by a particular type of impact.
-
D.
pollutionTolerance
Indicates the degree to which an entity can withstand or remain unaffected by environmental pollution without adverse effects.
-
E.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
- 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a979e4a48190a948165fb0f3b265 |
completed | April 20, 2026, 10:32 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:40 a.m.