Triple
T16604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mystic River |
E329
|
entity |
| Predicate | environmentalIssue |
P1006
|
FINISHED |
| Object | industrial pollution |
—
|
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: industrial pollution | Statement: [Mystic River, environmentalIssue, industrial pollution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: environmentalIssue Context triple: [Mystic River, environmentalIssue, industrial pollution]
-
A.
climate
Indicates a relationship where environmental or atmospheric conditions influence, shape, or characterize something (such as a place, system, or process).
-
B.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
C.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
D.
electrification
Indicates the process or state of providing electrical power or converting something to operate using electricity.
-
E.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
- F. None of above. chosen
Provenance (4 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fec1fe8819080da6f2c745dc8fd |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a241e933288190b02ef5369f7b8834 |
completed | Feb. 28, 2026, 1:16 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.