Triple
T6232257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Mesa |
E139383
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | El Cajon |
E201775
|
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: El Cajon | Statement: [La Mesa, adjacentTo, El Cajon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Cajon Context triple: [La Mesa, adjacentTo, El Cajon]
-
A.
El Cajon
chosen
El Cajon is a suburban city in Southern California’s East County region, located just east of San Diego.
-
B.
Escondido
Escondido is a city in northern San Diego County, California, known as one of the region’s older inland communities with a mix of suburban neighborhoods, agriculture, and historic downtown areas.
-
C.
Fullerton
Fullerton is a major Chicago Transit Authority station in the Lincoln Park neighborhood that serves multiple 'L' lines and connects riders to both local destinations and downtown Chicago.
-
D.
Fullerton
Fullerton is a city in northern Orange County, California, known for its historic downtown, California State University campus, and role as a suburban hub within the Greater Los Angeles metropolitan area.
-
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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ee6f088190bf72692eb8ffb761 |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3e5bd988190ad9b0af668f5b05c |
completed | March 27, 2026, 1:56 a.m. |
Created at: March 22, 2026, 4:22 p.m.