Triple
T110895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Andreas Fault |
E2244
|
entity |
| Predicate | maximumObservedOffset |
P7351
|
FINISHED |
| Object | several meters in single events |
—
|
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: several meters in single events | Statement: [San Andreas Fault, maximumObservedOffset, several meters in single events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumObservedOffset Context triple: [San Andreas Fault, maximumObservedOffset, several meters in single events]
-
A.
maximumService
Indicates that an entity provides the highest allowable or achievable level of service within a given context or system.
-
B.
isMaximumWhen
Indicates that a quantity or function reaches its greatest possible value under specified conditions or at a particular point.
-
C.
maximumDepth
Indicates the greatest extent or deepest level reached by something within a given context or structure.
-
D.
maximumIntensity
Indicates the greatest level or strength that a quantity, effect, or signal can reach within a given context.
-
E.
isLargestOf
Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a258b30f6c8190be2181f30c40e04d |
completed | Feb. 28, 2026, 2:53 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.