Triple
T21595782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonny Siebert |
E532893
|
entity |
| Predicate | teamCity |
P7424
|
FINISHED |
| Object | Oakland |
—
|
NE NERFINISHED |
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: Oakland | Statement: [Sonny Siebert, teamCity, Oakland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oakland Context triple: [Sonny Siebert, teamCity, Oakland]
-
A.
Oakland
Oakland is a neighborhood on Chicago’s South Side known for its historic residential architecture and proximity to the lakefront.
-
B.
Oakland
chosen
Oakland is a major port city in the San Francisco Bay Area known for its cultural diversity, progressive politics, and significant role in West Coast shipping and industry.
-
C.
Oakland
Oakland is a small village in northwestern Rhode Island known for its historic mill-era architecture and rural residential character within the town of Burrillville.
-
D.
Oakland
Oakland is a major Pittsburgh neighborhood known as the city’s educational and cultural hub, home to institutions like the University of Pittsburgh and Carnegie Mellon University.
-
E.
Oakland
Oakland is a small city in western Iowa, United States, known for its rural Midwestern character and local agricultural community.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefae15a7c819081627450ae726b0b |
completed | April 27, 2026, 5:57 a.m. |
Created at: April 16, 2026, 6:32 p.m.