Triple
T2869577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian River Lagoon |
E63525
|
entity |
| Predicate | facesThreat |
P43422
|
FINISHED |
| Object | nutrient 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: nutrient pollution | Statement: [Indian River Lagoon, facesThreat, nutrient pollution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facesThreat Context triple: [Indian River Lagoon, facesThreat, nutrient pollution]
-
A.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
B.
threatActorsMonitored
Indicates that one entity actively observes, tracks, or analyzes the activities or status of specified threat actors.
-
C.
threatTypeMonitored
Indicates that a particular type of threat is being actively observed, tracked, or watched for by some monitoring process or system.
-
D.
threatTypeAddressed
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
-
E.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfe15ff081908dd1dad62c292b2b |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde2cdcc48190827195d3ae70aa19 |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 10:02 p.m.