Triple
T9450861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acelhuate River |
E227885
|
entity |
| Predicate | sourceOfPollution |
P48801
|
FINISHED |
| Object | urban sewage |
—
|
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: urban sewage | Statement: [Acelhuate River, sourceOfPollution, urban sewage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sourceOfPollution Context triple: [Acelhuate River, sourceOfPollution, urban sewage]
-
A.
pollutionSource
chosen
Indicates that one entity is the origin or cause of pollution affecting another entity or environment.
-
B.
targetPollutant
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
C.
pollutant
Indicates that one entity is a substance or factor that contaminates or degrades the quality of another entity or environment.
-
D.
pollutantsCovered
Indicates that certain pollutants are included within the scope, protection, regulation, or consideration defined by a particular entity, policy, or agreement.
-
E.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f6649a48190b6844daa6202efe5 |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:51 p.m.