Triple
T18168113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Bailey |
E434947
|
entity |
| Predicate | financialCrisisCause |
P26452
|
FINISHED |
| Object | Uncle Billy losing bank deposit |
—
|
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: Uncle Billy losing bank deposit | Statement: [George Bailey, financialCrisisCause, Uncle Billy losing bank deposit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: financialCrisisCause Context triple: [George Bailey, financialCrisisCause, Uncle Billy losing bank deposit]
-
A.
majorCrisis
Indicates a severe, high-impact crisis or emergency situation affecting an entity or system.
-
B.
majorCrisisYear
Indicates the year in which a major crisis occurred or was most prominently manifested.
-
C.
causeOfDownfall
chosen
Indicates a factor, event, or agent that brings about the failure, ruin, or collapse of someone or something.
-
D.
crisisRelatedTo
Indicates a relationship where one situation, event, or condition is connected to, associated with, or relevant to a crisis.
-
E.
reasonForHyperinflation
Indicates that one entity is the cause or underlying factor leading to the occurrence of hyperinflation in another entity (typically an economy or currency).
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df52f8b08190ab2c4d76b510cd28 |
completed | April 19, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.