Triple
T36984585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aral Sea environmental disaster |
E914927
|
entity |
| Predicate | mainAffectedFeature |
P186854
|
FINISHED |
| Object | Aral Sea |
—
|
NE NERFINISHED |
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: Aral Sea | Statement: [Aral Sea environmental disaster, mainAffectedFeature, Aral Sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAffectedFeature Context triple: [Aral Sea environmental disaster, mainAffectedFeature, Aral Sea]
-
A.
frontAffected
Indicates that an action, event, or condition primarily impacts the front side or front-facing part of an entity.
-
B.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
C.
mainAffectedProvince
Indicates the province that is primarily impacted or influenced by a given event, action, or condition.
-
D.
featuresInfluence
Indicates that certain features or characteristics have an effect on or contribute to changes in other features, outcomes, or behaviors.
-
E.
affectedFunction
Indicates that one entity has an impact on, alters, or impairs the operation or behavior of another entity’s function.
- 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_69f76e8dd0408190b8b46da118ea5128 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fb154b5f8c819089103b41f51a1639 |
completed | May 6, 2026, 10:17 a.m. |
Created at: May 3, 2026, 4:14 p.m.