Triple
T24710215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpine Fault |
E612005
|
entity |
| Predicate | verticalUpliftRate |
P105662
|
FINISHED |
| Object | about 5–10 mm per year |
—
|
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: about 5–10 mm per year | Statement: [Alpine Fault, verticalUpliftRate, about 5–10 mm per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: verticalUpliftRate Context triple: [Alpine Fault, verticalUpliftRate, about 5–10 mm per year]
-
A.
upliftRate
chosen
Indicates the rate at which something is being raised or elevated over time, typically in a physical or quantitative sense.
-
B.
verticalDrop_m
Indicates the vertical distance, measured in meters, through which something drops or falls from a higher point to a lower point.
-
C.
verticalLocation
Indicates a vertical positional relationship where one entity is located above or below another along the up-down axis.
-
D.
verticalMigration
Indicates movement of an entity up and down along a vertical axis, typically in a repeated or cyclical pattern over time.
-
E.
targetVertical
Indicates that one entity is directed toward, aligned with, or intended for a specific vertical market, domain, or industry segment.
- 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_69e2c4d9c24c8190a3712d74327f0c6e |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:24 a.m.