Triple
T11477881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of La Verne |
E272068
|
entity |
| Predicate | hasAdditionalLocations |
P44057
|
FINISHED |
| Object | regional campuses in California |
—
|
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: regional campuses in California | Statement: [University of La Verne, hasAdditionalLocations, regional campuses in California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdditionalLocations Context triple: [University of La Verne, hasAdditionalLocations, regional campuses in California]
-
A.
additionalLocation
chosen
Indicates that an entity has one or more extra or secondary locations associated with it beyond its primary location.
-
B.
hasChainLocations
Indicates that an entity operates or is associated with multiple locations belonging to the same chain or network.
-
C.
hasAdditionalCounty
Indicates that an entity is associated with one or more counties beyond its primary or originally specified county.
-
D.
possibleLocation
Indicates that an entity may be located at, or could plausibly occur in, a specified place or spatial context.
-
E.
hasNumberOfLocalities
Indicates the relationship that specifies how many localities (e.g., towns, districts, or similar administrative units) are 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294e0fe08190b018e840146e27ca |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.