Triple
T34212758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US–California border |
E877701
|
entity |
| Predicate | hasSectionWithSurveyMonuments |
P200774
|
FINISHED |
| Object | California–Nevada border |
—
|
NE NERFINISHED |
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: California–Nevada border | Statement: [US–California border, hasSectionWithSurveyMonuments, California–Nevada border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionWithSurveyMonuments Context triple: [US–California border, hasSectionWithSurveyMonuments, California–Nevada border]
-
A.
hasMarkerOrMonument
Indicates that something possesses or is associated with a physical marker or monument commemorating it.
-
B.
hasScheduledMonument
Indicates that an entity is associated with, or contains, a site or structure officially designated as a scheduled monument.
-
C.
hasStoneMonument
Indicates that one entity possesses, contains, or features a stone monument associated with it.
-
D.
hasArchaeologicalSection
Indicates that one entity includes or is associated with a specific archaeological section or subdivision within it.
-
E.
hasWorkOnMonument
Indicates that an entity has created, contributed to, or performed work on a particular monument.
- 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_69f349b0b4bc819088c1552424089ee9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffac35ac5481908b6bdfd5bbe8c76e |
completed | May 9, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69ffabbfd2548190964c851496bbbaee |
completed | May 9, 2026, 9:48 p.m. |
| PDg | Predicate description generation | batch_69ffac34c5948190be36de5781d91da3 |
completed | May 9, 2026, 9:50 p.m. |
Created at: May 1, 2026, 1:55 a.m.