Triple
T25080039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wetumpka Impact Crater vicinity |
E628159
|
entity |
| Predicate | impactAge |
P159071
|
FINISHED |
| Object | Late Cretaceous |
—
|
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: Late Cretaceous | Statement: [Wetumpka Impact Crater vicinity, impactAge, Late Cretaceous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactAge Context triple: [Wetumpka Impact Crater vicinity, impactAge, Late Cretaceous]
-
A.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
B.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
C.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
D.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
E.
impactLevel
Indicates the degree or intensity of effect that one entity, action, or event has on another.
- 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_69e2ff2e73f881909992bf3eda5c25cb |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 18, 2026, 6:22 a.m.