Triple
T10107321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Francisco volcanic field |
E216352
|
entity |
| Predicate | otherMagmaType |
P80028
|
FINISHED |
| Object | andesite |
—
|
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: andesite | Statement: [San Francisco volcanic field, otherMagmaType, andesite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherMagmaType Context triple: [San Francisco volcanic field, otherMagmaType, andesite]
-
A.
typicalLavaType
Indicates the usual or characteristic type of lava associated with a given volcanic feature, eruption, or context.
-
B.
volcanismType
Indicates the specific kind or style of volcanic activity or processes associated with an entity.
-
C.
hasMagmaComposition
chosen
Indicates that something possesses or is characterized by a specific magma composition.
-
D.
lavaColor
Indicates the color attribute associated with a given lava substance or flow.
-
E.
typeOfVolcanicFeature
Indicates that one entity is classified as a specific kind or category of volcanic feature represented by the other 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0ca7f7c8190ba7ed37940aa933d |
completed | April 2, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9ed7e48190aa132ef8a69b49f9 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:03 p.m.