Triple
T27910004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebgen Lake |
E705898
|
entity |
| Predicate | hasNaturalDisaster |
P15089
|
FINISHED |
| Object | earthquake-induced seiche |
—
|
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: earthquake-induced seiche | Statement: [Hebgen Lake, hasNaturalDisaster, earthquake-induced seiche]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNaturalDisaster Context triple: [Hebgen Lake, hasNaturalDisaster, earthquake-induced seiche]
-
A.
hasDisaster
chosen
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
B.
hasNaturalHazardRisk
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
C.
hasNaturalPhenomenon
Indicates that a location, region, or environment possesses or is characterized by a particular natural phenomenon (such as a weather event, geological feature, or celestial occurrence).
-
D.
typeOfDisaster
Indicates that one entity is classified as a specific kind or category of disaster in relation to another entity.
-
E.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
- 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_69ef96b5aad08190be36a277c31e7004 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: April 27, 2026, 6:49 p.m.