Triple
T1322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California |
E26
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | San Francisco |
E242
|
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 Francisco | Statement: [California, hasMajorCity, San Francisco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Francisco Context triple: [California, hasMajorCity, San Francisco]
-
A.
San Francisco
chosen
San Francisco is a major coastal city in Northern California known for its hilly landscape, iconic Golden Gate Bridge, and role as a historic center of technology and counterculture.
-
B.
San Jose
San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
-
C.
Sacramento
Sacramento is the capital city of the U.S. state of California, known for its role as the state’s political center and its historic roots in the Gold Rush era.
-
D.
Los Angeles
Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
-
E.
Fresno
Fresno is a major agricultural and economic center in California’s San Joaquin Valley, known for its role in the state’s farming industry and its diverse urban population.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a234ccbac88190921bd0a15e4a7dbe |
completed | Feb. 28, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a24e51246c819098f53258d869ecde |
completed | Feb. 28, 2026, 2:09 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.