Triple
T5033628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Songhua River |
E113366
|
entity |
| Predicate | notablePollutionEvent |
P33268
|
FINISHED |
| Object | 2005 benzene spill in Jilin |
—
|
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: 2005 benzene spill in Jilin | Statement: [Songhua River, notablePollutionEvent, 2005 benzene spill in Jilin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePollutionEvent Context triple: [Songhua River, notablePollutionEvent, 2005 benzene spill in Jilin]
-
A.
environmentalEvent
chosen
Indicates an occurrence or phenomenon related to the natural environment, such as climatic, ecological, or geophysical changes or incidents.
-
B.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
-
C.
targetPollutant
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
D.
pollutionSource
Indicates that one entity is the origin or cause of pollution affecting another entity or environment.
-
E.
historicallyPollutedBy
Indicates that an entity has experienced pollution in the past as a result of actions or emissions from 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_69bd443775e48190a646ffbfc4334723 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73b68d8c8190b8e04fb406abdb0f |
completed | March 20, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.