Triple
T16449431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hood Mountain Regional Park |
E399513
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Santa Rosa, California |
E27583
|
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 Rosa, California | Statement: [Hood Mountain Regional Park, locatedNear, Santa Rosa, California]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Rosa, California Context triple: [Hood Mountain Regional Park, locatedNear, Santa Rosa, California]
-
A.
Santa Rosa
chosen
Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
-
B.
Santa Rosa
Santa Rosa is a residential barrio (neighborhood) within the municipality of Dorado, Puerto Rico.
-
C.
Santa Rosa
Santa Rosa is a rapidly urbanizing city in the Philippine province of Laguna, known as a major industrial, commercial, and residential hub in the Calabarzon region.
-
D.
Santa Rosa
Santa Rosa is the principal city and administrative center of Argentina’s La Pampa Province, known for its role as a regional hub in the country’s central plains.
-
E.
Santa Rosa
Santa Rosa is a small settlement located on Santa Cruz Island in the Galápagos archipelago of Ecuador.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cdfb0ec8190b75c4e6f4aceb200 |
completed | April 18, 2026, 7:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0060746c308190b67ff7c4646e10de |
completed | May 10, 2026, 10:39 a.m. |
Created at: April 10, 2026, 5:10 a.m.