Triple
T596162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauna Loa |
E17386
|
entity |
| Predicate | hasEruptionFrequency |
P12664
|
FINISHED |
| Object | every few decades in historical time |
—
|
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: every few decades in historical time | Statement: [Mauna Loa, hasEruptionFrequency, every few decades in historical time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEruptionFrequency Context triple: [Mauna Loa, hasEruptionFrequency, every few decades in historical time]
-
A.
eruptionFrequency
chosen
Indicates how often an eruption event occurs within a given time period.
-
B.
hasVolcanicActivity
Indicates that the subject exhibits or is associated with ongoing or past volcanic processes, such as eruptions, lava flows, or related geothermal activity.
-
C.
hasVolcano
Indicates that one entity possesses, contains, or is the location of a volcano.
-
D.
notableEruption
Indicates that a volcano or geothermal feature has experienced an eruption considered historically or scientifically significant.
-
E.
lastEruption
Indicates the time or event corresponding to the most recent eruption associated with a given 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd3e5e08190be95cb2009aad42d |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494ceeb7881909a91ed1a35d5bf0a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.