Triple
T23444224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President Tom Beck |
E565488
|
entity |
| Predicate | crisisTypeFaced |
P93977
|
FINISHED |
| Object | global extinction-level event |
—
|
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: global extinction-level event | Statement: [President Tom Beck, crisisTypeFaced, global extinction-level event]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crisisTypeFaced Context triple: [President Tom Beck, crisisTypeFaced, global extinction-level event]
-
A.
typeOfCrisis
chosen
Indicates the specific category or nature of a crisis that an entity is experiencing or associated with.
-
B.
typeOfCrisisManagement
Indicates the specific approach or method used to manage, respond to, or resolve a crisis situation.
-
C.
crisisRelatedTo
Indicates a relationship where one situation, event, or condition is connected to, associated with, or relevant to a crisis.
-
D.
crisisContext
Indicates that the relationship or action occurs within, is shaped by, or is specifically relevant to a crisis situation or emergency context.
-
E.
crisisManagement
Indicates the relationship in which an entity plans for, responds to, and mitigates the impact of disruptive or emergency situations.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64717d08190a2c25e7bbfc17a2f |
completed | April 29, 2026, 6:33 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:51 p.m.