Triple
T255803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego International Airport |
E5434
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | San Diego |
E36927
|
NE 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: San Diego | Statement: [San Diego International Airport, locatedIn, San Diego]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Diego Context triple: [San Diego International Airport, locatedIn, San Diego]
-
A.
San Diego
chosen
San Diego is a large coastal city in Southern California known for its mild climate, beaches, naval base, and proximity to the Mexican border.
-
B.
Anaheim
Anaheim is a major city in Orange County, California, best known as the home of the Disneyland Resort and a significant hub for tourism and entertainment in the region.
-
C.
Carlsbad
Carlsbad is a coastal city in northern San Diego County, California, known for its beaches, family attractions like LEGOLAND California, and affluent residential communities.
-
D.
Chula Vista
Chula Vista is a large coastal city in Southern California known for its diverse communities, rapid suburban growth, and proximity to both downtown San Diego and the U.S.–Mexico border.
-
E.
Irvine
Irvine is a master-planned city in Orange County, California, known for its affluent residential communities, strong public schools, and concentration of technology and education industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d5669008190978bbd7308be11f7 |
completed | Feb. 28, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a52383450081908b945646a3e231c2 |
completed | March 2, 2026, 5:43 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.