Triple
T22092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern California |
E439
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
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.
|
E30312
|
NE FINISHED |
How this triple was built (4 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: Monterey | Statement: [Northern California, hasMajorCity, Monterey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monterey Context triple: [Northern California, hasMajorCity, Monterey]
-
A.
Santa Rosa
Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
-
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.
Salinas
Salinas is a prominent agricultural city in Northern California, often called the "Salad Bowl of the World" and known as the birthplace of author John Steinbeck.
-
E.
San Jose
San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Monterey Triple: [Northern California, hasMajorCity, Monterey]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monterey Target entity description: 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.
-
A.
Santa Rosa
Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
-
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.
Salinas
Salinas is a prominent agricultural city in Northern California, often called the "Salad Bowl of the World" and known as the birthplace of author John Steinbeck.
-
E.
San Jose
San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
- F. None of above. chosen
Provenance (5 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a2466ab310819091842a0ea9fd25de |
completed | Feb. 28, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36729974c819091d999022059c4a7 |
completed | Feb. 28, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69a367a0e2c88190bd1671f69a2cbf38 |
completed | Feb. 28, 2026, 10:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a367fab3408190865f50c240379d41 |
completed | Feb. 28, 2026, 10:11 p.m. |
Created at: Feb. 28, 2026, 1:34 a.m.