Triple
T12760371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1968 Borrego Mountain earthquake |
E304975
|
entity |
| Predicate | economicLosses |
P25888
|
FINISHED |
| Object | millions of US dollars |
—
|
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: millions of US dollars | Statement: [1968 Borrego Mountain earthquake, economicLosses, millions of US dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicLosses Context triple: [1968 Borrego Mountain earthquake, economicLosses, millions of US dollars]
-
A.
economicDamage
Indicates that one entity causes or experiences financial loss, harm, or negative economic impact as a result of another entity or event.
-
B.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
C.
economicFunction
Indicates the role or purpose an entity serves within an economic system, such as how it contributes to production, distribution, or consumption of goods and services.
-
D.
economicDamageApprox
chosen
Indicates that one entity has caused or is associated with an estimated or approximate amount of economic damage to another entity or system.
-
E.
economicDamageRank
Indicates the relative severity or position of an entity in terms of the economic damage it causes or experiences compared to others.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8e44188190840cd23d380bf23d |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.