Triple
T626716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alameda County |
E15834
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Alameda |
E180395
|
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: Alameda | Statement: [Alameda County, containsCity, Alameda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alameda Context triple: [Alameda County, containsCity, Alameda]
-
A.
Alameda, California
chosen
Alameda, California is a Bay Area island city adjacent to Oakland known for its historic Victorian architecture, waterfront parks, and residential neighborhoods.
-
B.
Santa Clara
Santa Clara is a Silicon Valley city in California known for its high-tech industry presence, Levi’s Stadium, and Santa Clara University.
-
C.
Vallejo
Vallejo is a waterfront city in the San Francisco Bay Area known for its former Mare Island Naval Shipyard and diverse, working-class community.
-
D.
Daly City
Daly City is a suburban city just south of San Francisco in San Mateo County, California, known for its diverse population and role as a major residential and commercial hub in the Bay Area.
-
E.
San Mateo
San Mateo is a city in California’s San Francisco Bay Area, known for its suburban neighborhoods, parks, and role as a commercial and residential hub on the Peninsula.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e587c448190987943a6aad209d1 |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad606954e8819086ae3e46f3628483 |
completed | March 8, 2026, 11:41 a.m. |
Created at: March 1, 2026, 7:35 p.m.