Triple
T22093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern California |
E439
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Eureka
Eureka is a historic coastal city in Northern California known for its Victorian architecture, maritime heritage, and role as a regional cultural and economic center.
|
E3001
|
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: Eureka | Statement: [Northern California, hasMajorCity, Eureka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eureka Context triple: [Northern California, hasMajorCity, Eureka]
-
A.
Douglas
Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
-
B.
Turtle Bay
Turtle Bay is a neighborhood on Manhattan’s East Side in New York City, best known as the site of the United Nations Headquarters.
-
C.
Carnegie
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
-
D.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
E.
Nelson
Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
- 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: Eureka Triple: [Northern California, hasMajorCity, Eureka]
Generated description
Eureka is a historic coastal city in Northern California known for its Victorian architecture, maritime heritage, and role as a regional cultural and economic center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eureka Target entity description: Eureka is a historic coastal city in Northern California known for its Victorian architecture, maritime heritage, and role as a regional cultural and economic center.
-
A.
Douglas
Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
-
B.
Turtle Bay
Turtle Bay is a neighborhood on Manhattan’s East Side in New York City, best known as the site of the United Nations Headquarters.
-
C.
Carnegie
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
-
D.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
E.
Nelson
Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
- 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_69a24e59b35c8190a192ed9095a8756d |
completed | Feb. 28, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69a24edf06688190963f6812d173d56e |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a24fec71908190813a1e322bbbdbb6 |
completed | Feb. 28, 2026, 2:16 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.