Triple
T12064064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California State Route 84 |
E287247
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Oakley |
E477680
|
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: Oakley | Statement: [California State Route 84, servesCity, Oakley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oakley Context triple: [California State Route 84, servesCity, Oakley]
-
A.
Oakley
chosen
Oakley is a city in Contra Costa County, California, located in the eastern San Francisco Bay Area.
-
B.
Oakley
Oakley is a surname most notably associated with Violet Oakley, an American artist and pioneering female muralist of the early 20th century.
-
C.
Oakley (former)
Oakley (former) is a sports performance and lifestyle brand best known for its high-tech eyewear, apparel, and accessories popular among professional athletes and outdoor enthusiasts.
-
D.
Koss
Koss is a Norwegian surname most notably associated with Johann Olav Koss, the Olympic gold medal–winning speed skater and humanitarian.
-
E.
K2 Sports
K2 Sports is an American sporting goods company best known for its skis, snowboards, and other winter sports equipment.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90440dd988190ae2b80367aceb6f7 |
completed | April 10, 2026, 2:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f654eb1881908d656009f1362ecf |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.