Triple
T21197375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Betsy (1965) |
E522360
|
entity |
| Predicate | damageCostNote |
P143521
|
FINISHED |
| Object | costs in 1965 USD |
—
|
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: costs in 1965 USD | Statement: [Hurricane Betsy (1965), damageCostNote, costs in 1965 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageCostNote Context triple: [Hurricane Betsy (1965), damageCostNote, costs in 1965 USD]
-
A.
damageLeadsTo
Indicates that one instance of damage causally results in or contributes to another specified outcome or condition.
-
B.
damageEffect
Indicates that one entity causes harm, reduction, or deterioration to another entity or its properties.
-
C.
damageAssociatedWith
Indicates a relationship where one entity is linked to causing, contributing to, or being responsible for damage affecting another entity.
-
D.
damageAssessedBy
Indicates that the extent or nature of damage to something has been evaluated or determined by a particular agent or authority.
-
E.
damageDescription
Indicates a textual description of the nature, extent, or characteristics of damage associated with an entity or event.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333c9bac8190a203802a8b8e4143 |
completed | April 21, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5fa92a2448190896c022dd27511ad |
completed | April 20, 2026, 10:06 a.m. |
Created at: April 16, 2026, 3:11 p.m.