Triple
T959764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central California |
E20707
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Santa Cruz |
E75429
|
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: Santa Cruz | Statement: [Central California, contains, Santa Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz Context triple: [Central California, contains, Santa Cruz]
-
A.
Santa Cruz
Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
-
B.
Santa Cruz, California
chosen
Santa Cruz, California is a coastal city in Northern California known for its surf culture, beach boardwalk, and progressive university community.
-
C.
San Rafael
San Rafael is a city in the North Bay region of the San Francisco Bay Area in California, known for its historic downtown and role as a cultural and economic hub of Marin County.
-
D.
Monterey
Monterey is a historic coastal city in Northern California known for its scenic bay, marine life, and former prominence as a sardine-canning and fishing center.
-
E.
Monterey
Monterey is a small rural town in Berkshire County, western Massachusetts, known for its scenic landscapes, forests, and lakes.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b412f9f48190be123e8c20f38962 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0b24844819090904b831c73495c |
completed | March 8, 2026, 4:15 p.m. |
Created at: March 1, 2026, 7:40 p.m.