Triple
T3099839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calexico |
E64688
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Imperial County |
E27589
|
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: Imperial County | Statement: [Calexico, county, Imperial County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Imperial County Context triple: [Calexico, county, Imperial County]
-
A.
Imperial County
chosen
Imperial County is a largely agricultural and desert county in southeastern California, bordering Mexico and known for the Imperial Valley and the Salton Sea.
-
B.
Mariposa County
Mariposa County is a rural county in central California best known as the gateway to much of Yosemite National Park and the Sierra Nevada.
-
C.
Lassen County
Lassen County is a rural county in northeastern California known for its volcanic landscapes, high desert terrain, and proximity to Lassen Volcanic National Park.
-
D.
Kern County
Kern County is a large, oil- and agriculture-rich county in California’s southern Central Valley that includes cities such as Bakersfield and is a major hub for energy production.
-
E.
San Bernardino County
San Bernardino County is a large county in Southern California known for its vast desert landscapes, portions of the Mojave Desert, and rapidly growing urban and suburban communities.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada26b03a081909cf187b9a8f805ce |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2037cc5fc819084a441ebb045142b |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:03 p.m.